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QGIS: Understanding and Using Attribute Data, Queries, and Analysis
 
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This webinar will introduce novice QGIS and GIS users to simple analysis tools that take advantage of attribute data.
Views: 9858 VTgeospatial
Excel 2013 Data Analytics Webinar: How to Structure and Analyze large data with Power BI tools
 
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In this 1 hour Webinar, Dr. Nitin Paranjape (Office MVP) will show you how to structure and analyze large amount of data in just a few seconds using Excel 2013's Power BI features: Pivot Table, Power Pivot, Power Query and Power View. Topics covered: - Purpose of data analysis (2:30) - Data Analysis process (4:06) - Good data vs Bad data (5:34) - Rules for Good data (9:05) - Common Examples of badly formatted data (10:41) - How to handle cross-tab data with Power Query (14:44) - Gather data from the web with (18:57) - Power Query's Data Catalogue Search (20:00) - Split Column by Delimiter (20:05) - Refresh live data in Power Query (23:20) - Summarize Data in Pivot Tables (24:26) - Do Calculation right inside Pivot Tables with Calculated Fields (27:33) - Avoid Wrong calculations with Get Pivot Data (29:10) - Data Visualization with Conditional Formatting & Quick Analysis (31:12) - Limitations of Pivot Table (34:38) - Why use Power Pivot (35:19) - Analyze 43 million rows of data within Power Pivot (36:40) - Build interactive dashboards with Power View (41:42) - Share Power View reports on Sharepoint (47:15) - Manage viewing rights with Excel's Browser View option - Create 3D map reports in Power Map (49:38) - Power BI Preview (55:20) - Summary: Which tool to use in which scenario? (59:03) - Notes to Developers (59:17) This is a recording of the Data Analytics Webinar for Microsoft, powered by Economic Times. The webinar was conducted by Dr. Nitin Paranjape, Office MVP and Microsoft Regional Director.
Views: 14531 Efficiency 365
Why Use R? - R Tidyverse Reporting and Analytics for Excel Users
 
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https://www.datastrategywithjonathan.com Free YouTube Playlist https://www.youtube.com/playlist?list=PL8ncIDIP_e6vQ0uQofezvKv3yPnL5Unxe From Excel To Big Data and Interactive Dashboard Visualizations in 5 Hours If you use Excel for any type of reporting or analytics then this course is for you. There are a lot of great courses teaching R for statistical analysis and data science that can sometimes make R seem a bit too advanced for every day use. Also since there are many different ways of using R that can often add to the confusion. The reality is that R can be used to make your every day reporting analytics that you do in Excel much faster and easier without requiring any complex statistical techniques while at the same time giving you a solid foundation to expand into those areas if you so wish. This course uses the Tidyverse standards for using R which provides a single, comprehensive and easy to understand method for using R without complicating things via multiple methods. It's designed to build upon the the skills you are already familiar with in Excel to shortcut your learning journey. If you're looking to learn Advanced Excel, Excel VBA or Databases then you need to check out this video series. In this videos series, I will show you how to use Microsoft Excel in different ways that will make you far more effective at working with data. I'm also going to expand your knowledge beyond Excel and show you tips, tricks, and tools from other top data analytics tools such as R Tidyverse, Python, Data Visualisation tools such as Tableau, Qlik View, Qlik Sense, Plotly, AWS Quick Sight and others. We'll start to touch on areas such as big data, machine learning, and cloud computing and see how you can develop your data skills to get involved in these exciting areas. Excel Formulas such as vlookup and sumifs are some of the top reasons for slow spreadsheets. Alternatives for vlookup include power query (Excel 2010 and Excel 2013) which has recently been renamed to Get and Transform in Excel 2016. Large and complex vlookup formulas can be also done very efficiently in R. Using the R Tidyverse libraries you can use the join functions to merge millions of records effortlessly. In comparison to Excel Vlookup, R Tidyverse Join can pull on multiple columns all at the same time. Microsoft Excel Power Query and R Tidyverse Joins are similar to the joins that you do in databases / SQL. The benefit that they have over relational databases such as Microsoft Access, Microsoft SQL Server, MySQL, etc is that they work in memory so they are actually much faster than a database. Also since they are part of an analytics tool instead of a database it is much faster and easier to build your analysis and queries all in the same tools. My very first R Tidyverse program was written to replace a Microsoft Access VBA solution which was becoming complicated and slow. Note that Microsoft Access is very limited in analytics functions and is missing things as simple as Median. Even though I had to learn R programming from scratch and completely re-write the Microsoft Access VBA solution it was so much easier and faster. It blew my mind how much easier R programming with R Tidyverse was than Microsoft Access VBA or Microsoft Excel VBA. If you have any VBA skills or are looking to learn VBA you should definitely checkout my videos on R Tidyverse. To understand why R Tidyverse is so much easier to work with than VBA. R Tidyverse is designed to work directly with your data. So If you want to add a calculated column that’s around one line of script. In Excel VBA, the VBA is used to control the DOM (Document Object Model). In Excel that means that you VBA controls things like cells and sheets. This means your VBA is designed to capture the steps that you would normally do manually in Microsoft Excel or Microsoft Access. VBA is not actually designed to work directly with your data. Note the most efficient path is to reduce the data pulled down from the database in the first place. This is referring to the amount of data you are pulling down from your data warehouse or data lake. It makes no sense to pull data from a data warehouse / data lake to pull into another database to query add joins / lookups to then pull it into Excel or other analysis tool. Often analyst build these intermediate databases because they either don’t have control of the data warehouse or they need to join additional information. All of these operations are done significantly faster in a tool such as R Tidyverse or Microsoft Excel Power Query.
Views: 16008 Jonathan Ng
Get in-depth insights with AI and machine learning data analysis tools
 
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Use quick insights and natural language queries to explore your data and analyze customer behavior on a large scale. Discover how powerful artificial intelligence (AI) and machine learning capabilities in Power BI give you more value from your data. Learn more: https://powerbi.microsoft.com/en-us/
Views: 827 Microsoft Cloud
E-DAB 06: The Magic of Power Query to Import, Transform & Load Data
 
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Download all files to follow along with video and do homework is zipped folder here: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/DownloadFilesForEDAB06.zip To download individual files, visit class web site here: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/EDAB.htm This video teaches about the basics of how to use Power Query to import, clean, transform and load data. This class : Data Analysis & Business Intelligence Made Easy with Excel Power Tools - Excel Data Analysis Basics = E-DAB Class – Sponsored by YouTube and taught by Mike Girvin, Highline College Instructor, Microsoft Excel MVP and founder of the excelisfun channel at YouTube. This is a free educational resource for people how want to learn about the Basics of Data Analysis and Business Intelligence using Microsoft Power Tools such as, PivotTables, Power Query, Power Pivot, Power BI Desktop and more. Topics: 1. (00:12) Introduction 2. (01:14) Power Query Icon as Magic 3. (02:19) Files to download and unzip folder 4. (03:12) What is Power Query? What does Power Query do? 5. (05:19) Example 1: Import Text File to create report and chart. Then get a new Text File next month and everything will update. 6. (07:11) A complete introduction to Power Query. 7. (12:59) Two methods to update report when you get a new Text file: 1) Edit Query, or 2) Duplicate Query. 8. (15:02) Example 2: Clean Bad Data in an Excel Sheet, Load to Excel Sheet, Build PivotTable. Then add new data and refresh the Query and the PivotTable Cache. 9. (20:42) Example 3: Import multiple Text Files from Folder and Append into single Proper Data Set. 10. (20:30) Summary The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 15393 ExcelIsFun
Microsoft Power Tools for Data Analysis: Dashboards & Reports. Class Introduction Video. MSPTDA #01.
 
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Download Excel File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/Intro/001-MSPTDA-IntroToClass.xlsx Download pdf Notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/Intro/001-MSPTDA-IntroToClass.pdf This video introduces the topics that will be covered in this Highline College BI 348 Class: Name of Class: BI 348 – Microsoft Power Tools for Data Analysis: • Power Query • Power Pivot • DAX • Power BI Desktop • Excel For Creating: • Data Models, Reports, Dashboards and Analytics Taught by Mike excelisfun Girvin, Excel MVP 2013-2018 • A class about connecting to multiple source of data, transforming the data into a refreshable & dynamic data model, and building reports and dashboards to provide insightful and actionable information. Prerequisites for this class: • Busn 216: Excel Basics, https://www.youtube.com/playlist?list=PLrRPvpgDmw0n34OMHeS94epMaX_Y8Tu1k • Busn 218: Advanced Excel, https://www.youtube.com/playlist?list=PLrRPvpgDmw0lcTfXZV1AYEkeslJJcWNKw • Busn 210: Business Statistics, https://www.youtube.com/playlist?list=PLrRPvpgDmw0ngx_uPhvasTbOWLOztsaBj What Version of Excel: • Office 365 (updated each month) What Version of Power BI Desktop: • Free Tool we will download (update each month) Over View of Topics for the class: 1. Data Analysis / Business Intelligence terms and concepts that we will learn in this class: • Proper Data Set • Fact Table • Dimension Tables • Relationships • Star Schema • ETL • Measures • Dashboards • SQL • Data Warehousing   2. Learn how to use Excel Power Query: • Import Data from multiple sources • Clean and Transform Data • Create Data Components for Star Schema Data Models • Load Data To Excel, the Data Model and Connection Only • Replace Complicated Excel Solutions with Power Query Solution • Use the Power query User Interface to create Power Query Solutions • Learn about the Case Sensitive, Function-based M Code Language that is behind the scenes in Power Query 3. Learn how to use Excel Power Pivot: • Excel Power Pivot provides: i. Data Model where we can have multiple tables, formulas and relationships (Star Schema) ii. Columnar Database to hold "Big Data" and process quickly over that "Big Data" iii. New Formula Language called DAX: 1. Many More Calculations than in Standard PivotTable 2. Build One Formula that can work in many reports 3. Add Number Formatting to Formulas • Excel Power Pivot to: i. Replace VLOOKUP Formulas and Single Flat PivotTable Data Source with Multiple Tables, Relationships in the Data Model to create more efficient Reports & Dashboards ii. Use Power Pivot Columnar Database to hold millions of rows of data iii. DAX formulas have more Power than Standard PivotTable Calculations 4. Learn about Building Star Schema Data Models: a. Why they are important in Power Pivot and Power BI Desktop b. How to build them using: i. Power Query ii. Power Pivot iii. DAX iv. Power BI Desktop 5. Learn how to author DAX Formulas for Excel’s Power Pivot & Power BI Desktop: a. Calculated Column Formulas for Data Model b. Measure Formulas for PivotTables c. DAX Functions like SUMX, CALCULATE, RELATED, and Much More… d. Lean why we must create Explicit rather than Implicit formulas e. Learn how Row Context works in formulas f. Learn how Filter Context works in formulas g. Learn about Scalar & Table Functions h. Use DAX Studio to visualize and analyze DAX Formulas 6. Learn how to use Power BI Desktop: a. Power Query to import, clean, transform and create Star Schema Data Models b. Create Relationships c. Create DAX Formulas d. Build Interactive Visualizations e. Build Dashboards   7. Learn how to use Excel: • Spreadsheet Formulas & Functions • Standard PivotTables • Power Query • Power Pivot • Build Data Model PivotTables and the resultant Reports, Dashboards and Analytics 8. Building Refreshable, Insightful Dashboards a. Build Excel Dashboards b. Build Power BI Dashboards 9. Case Studies to practice using Power Pivot & Power BI Desktop for Reporting, Building Dashboards and Building Business Analytics Solutions The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 33446 ExcelIsFun
Using Tools to Analyze SQL Server Query Performance
 
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SQLServerZest.com
Views: 8196 Suresh Raavi
Skyline TerraExplorer 6.5 Feature Demo
 
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The new release of TerraExplorer v6.5 introduces support for stream-optimized and fully textured urban models (3DML) that can be queried and analyzed. New terrain analysis tools expand TerraExplorer's powerful viewshed capabilities (3D Viewshed Analysis and Viewshed Query) and increase shadow display/analysis options (Shadow Query and Selection Shadow). Other new analysis tools provide for easier visualization of slope data (Slope Query), and for dynamic comparison of imagery layers or of 3D View snapshots. For more information, visit us at http://www.skylineglobe.com
Views: 8104 skylinesoft
Skyline TerraExplorer 6.1 - Measurement and Analysis Tools
 
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Featuring Skyline's TerraExplorer measurement and analysis tools including: Area Measurement, Modify Terrain, Volume Analysis, Timespan, Viewshed on Route, and Flood Analysis, this video demonstrates how Skyline's TerraExplorer application can be used in planning the construction of a new apartment building. For more information, visit us at http://www.skylineglobe.com
Views: 3667 skylinesoft
MSPTDA 23: Two Fact Tables? DAX, Power Query or Worksheet Formulas to Convert to 1 Fact Table
 
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All 9 files for video in this zipped folder: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/DataModeling/MSPTDA-23-DownloadAllFiles.zip Download file individually at class web site: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/DataModeling/DataModeling.htm pfd notes for Video #23: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/DataModeling/023-MSPTDA-TwoFactTables.pdf In this video learn about how to convert 2 Fact Tables into one with DAX, Worksheet Formulas or Power Query Comprehensive Microsoft Power Tools for Data Analysis Class, BI 348, taught by Mike Girvin, Excel MVP and Highline College Professor. Topics: 1. (00:16) Introduction 2. (02:35) Excel Worksheet Formula Solution 3. (05:01) How do we allocate Discount from Invoice Grain to Invoice Line Grain? 4. (05:45) Worksheet Formula for Total Invoice Sales at Invoice Grain using SUMPRODUCT function 5. (09:23) Worksheet Formula for % Sales Discount at Invoice Grain using division 6. (10:00) Worksheet Formula for Line Discount at Invoice Line Grain using VLOOKUP and multiplication 7. (12:12) How do we allocate Shipping from Invoice Grain to Invoice Line Grain? 8. (13:27) Worksheet Formula for Invoice Line Shipping Weight at Invoice Line Grain using VLOOKUP and multiplication 9. (14:30) Worksheet Formula for Invoice Weight at Invoice Grain using SUMIFS 10. (15:04) Worksheet Formula for Line Shipping at Invoice Line Grain using VLOOKUP and multiplication 11. (16:50) Create Excel Reports at Product Grain. 12. (17:03) Standard PivotTable Report 13. (17:53) Worksheet Formula Report 14. (21:26) DAX Formula Solution in Power Pivot 15. (22:30) Look at Data Model and preview of DAX Formulas and functions SUMX, RELATED and RELATEDTABLE 16. (24:30) Bring Excel Tables into Data Model 17. (25:15) Create Relationships between tables 18. (26:23) How to Allocate Invoice Grain Numbers to Invoice Line Grain Numbers 19. (26:56) DAX Formula for Total Invoice Sales at Invoice Grain using SUMX and RELATEDTABLE functions 20. (29:40) DAX Formula for % Sales Discount at Invoice Grain using DIVIDE function 21. (30:50) DAX Formula for Line Discount at Invoice Line Grain using RELATED function and multiplication 22. (31:57) DAX Measure for Total Discount 23. (32:39) Data Model PivotTable Report for Product Discount 24. (33:08) How do we allocate Shipping from Invoice Grain to Invoice Line Grain?+ 25. (34:22) DAX Formula for Invoice Weight at Invoice Grain using SUMX, RELATEDTABLE and RELATED. 26. (35:56) Visuals to understand how DAX Formula with SUMX, REALTEDTABLE and RELATED are working to traverse multiple relationships in one formula. This helps illustrates the Power of DAX for Business Calculations. 27. (36:52) DAX Formula for Line Shipping at Invoice Line Grain using RELATED and multiplication and division. Three RELATED function in one formula 28. (39:03) DAX Measure for Total Shipping 29. (39:25) Final Data Model PivotTable 30. (40:22) Power Query Solution in Power BI Desktop 31. (41:09) Why Two Fact Tables will not work with all Dimension Tables for Reporting. 32. (43:05) Summary and visuals of steps we need to perform 33. (44:12) Create blank Power BI Desktop file 34. (44:40) Import Two Fact Table Data Model from Power Pivot 35. (45:40) Power Query Formula to calculate Sales at Invoice Line Grain using Table.AddColumn function 36. (46:53) Power Query Merge to lookup Product Weight at Invoice Line Grain 37. (47:26) Power Query Formula to calculate Product Shipping Weight at Invoice Line Grain using Table.AddColumn function 38. (47:42) Power Query Group By feature to aggregate Invoice Sales, Invoice Shipping Weight and all rows in Invoice Line Grain Table for each Invoice Number. 39. (49:52) Power Query Merge to pull Invoice Grain Shipping & Discount numbers, as well as to pull the Invoice Level Dimensions of Date and Sales Rep ID into the current step in the query (later after expanding it will be the Invoice Line Grain). 40. (50:52) Power Query Formula for % Sales Discount at Invoice Grain using Table.AddColumn function 41. (52:11) Expand to get back to Invoice Line Grain 42. (52:31) Note about Unit Price and how it is stored as a Fact because it changes so often. 43. (54:16) Power Query Formula for Line Discount at Invoice Line Grain using Table.AddColumn function and Number.Round 44. (54:49) Power Query Formula for Line Shipping at Invoice Line Grain using Custom Column using Table.AddColumn function and Number.Round 45. (57:23) Remove all column we do not need in final Fact Table 46. (58:08) Load Tables to Data Model, except Invoice Level Table. 47. (59:15) Create DAX Measures for Shipping, Discounts and Sales 48. (01:00:10) Create % DAX Measures for Shipping and Discount as a percent of sales. Use the DIVIDE DAX Function. 49. (01:01:15) Hide Columns from Report View 50. (01:01:33) Look at Final Data Model 51. (01:01:47) Create Visualization in Power BI Desktop 52. (01:04:40) Summary
Views: 3644 ExcelIsFun
E-DAB 01: What is Data Analysis & Business Intelligence?
 
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Download Notes from Video: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-01-IntroductionToClass.pptx Full class web site: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/EDAB.htm This video is an introduction to the : Data Analysis & Business Intelligence Made Easy with Excel Power Tools - Excel Data Analysis Basics = E-DAB Class – Sponsored by YouTube and taught by Mike Girvin, Highline College Instructor, Microsoft Excel MVP and founder of the excelisfun channel at YouTube. This is a free educational resource for people how want to learn about the Basics of Data Analysis and Business Intelligence using Microsoft Power Tools such as, PivotTables, Power Query, Power Pivot, Power BI Des Topics: 1. (00:00) Intro Song 2. (00:12) Intro to First video in class 3. (01:36) Instructor 4. (01:59) Scope of Class 5. (02:40) Version of Excel 6. (03:30) Define Data Analysis & Business Intelligence 7. (06:00) Goals of Class 8. (09:31) Videos Topics Presented In Class 9. (10:33) Files for you to Download 10. (10:59) What You Will Gain After Taking This Class 11. (12:17) Summary The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 22203 ExcelIsFun
Data Analyst Job Description | What 4 Skills Will You Need To Be A Data Analyst?
 
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In this video we are going to define the job description of a data analyst, what a data analyst does, and the best online course to become a data analyst. ► Full Playlist Explaining Data Jargon ( http://bit.ly/2mB4G0N ) ► Top 4 Best Laptops for Data Analysts ( https://youtu.be/Vtk50Um_yxA ) ► Break Into the Data Industry with the best data analytics online learning resources from Edureka! ( http://bit.ly/2yCbsac ) --- affiliate link to help support this channel!^ Currently the average pay for a data analyst is $76,419 on the button, according to glassdoor I receive a lot of questions about what it takes to become a data analyst and what is a data analyst. Clearing up what a data analyst does everyday and what that description means to someone looking to enter the data science industry What will you actually be asked to do on the day to day as a data analyst. ► Top 4 Responsibilities in the Daily Life of a Data Analyst: 1 ) Mathematics Although mathematics only makes up about 20% of the day to day life of a data analyst. It is still important to have a strong understanding of the foundations of mathematics. - Addition - Subtraction - Multiplication - Division - Most Importantly --- Statistics Data analytics is all about statistics. Most of the statistics will be handled by the tools you are working with, but in order to be a great data analyst it is best to know why the tools are producing specific results. A strong understanding of statistics will be useful to you. 2 ) Computer Programming You must be able to work proficiently in one or more computer programming languages. This make up for roughly 60%-70% of your daily work. in order to analyze data it must be queried (drawn) from a large data warehouse. You will use computer programming languages such as SQL, Python, and R to query data. Before we move on let me define the term Query, if it does not resonate with you. You need strong computer programming skills in order to accomplish this task. As a data analyst you will do a lot of drawing and analyzing data. ► For more info on databases, SQL, and other jargon check out our Video Series on Data Jargon ( https://www.youtube.com/playlist?list=PL_9qmWdi19yDhnzqVCAhA4ALqDoqjeUOr ) 3 ) Know the Tools of the Trade Once you query data from the database onto your workspace you will begin to utilize data analytics tools to process, scrub, and analyze data (data Jargon explained on our Video series ^^^). You will be able to perform these tasks by using tools like Hadoop, Open Refine, Tableau, Apache Spark, etc... As you process the data you will begin to see connections between the data sets. You will see some of the following errors and you will want to remove these in order to ensure that your data analysis is accurate: - Duplicated data - Improperly formatted data - Incomplete data - Inaccurate data - This data will corrupt your findings and could possibly lose you client or employer millions of dollars. Make sure you know how to use those data analytics tools WELL! 4 ) Communicate and Present Insights Data Analyst will also be called upon to clearly and consciously present your research to clients, managers, or executives. Ok, now I know you are curious if you are capable of learning all of these crucial skills. Yes, you can, but there is a clause. You have to learn from the best. The guys over at Edureka.co are the leading professionals in the big data training industry. Based out of India, home to over 101,000 individuals in the data science industry (at the time of this writing). They are eager to make a way for themselves in the new digital economy. They are on the cutting edge of data analytics and eager to teach it to anyone worldwide. Testimonies of increased salaries, new employment, and 597,089 (updated) satisfied learners make edureka the best choice to learn the skills you need in the data industry. Question is will you actually do it. Imagine deregulating yourself for the data industry. Right now, it is a black hole, you don't know what's inside, but it is screaming opportunity from the darkness. TURN ON THE LIGHT and break into the data industry. A future proof opportunity for the next decade and beyond. ► Edureka Big Data Masters Program ( http://bit.ly/2yCbsac ) affiliate link^ ------- SOCIAL Twitter ► @jobsinthefuture Facebook ►/jobsinthefuture Instagram ►@Jobsinthefuture WHERE I LEARN: (affiliate links) Lynda.com ► http://bit.ly/2rQB2u4 edX.org ► http://fxo.co/4y00 MY FAVORITE GEAR: (affiliate links) Camera ► http://amzn.to/2BWvE9o CamStand ► http://amzn.to/2BWsv9M Computer ► http://amzn.to/2zPeLvs Mouse ► http://amzn.to/2C0T9hq TubeBuddy ► https://www.tubebuddy.com/bengkaiser ► Download the Ultimate Guide Now! ( https://www.getdrip.com/forms/883303253/submissions/new ) Thanks for Supporting Our Channel!
Views: 122309 Ben G Kaiser
Module 1: Data Analysis in Excel
 
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This video is part of the Analyzing and Visualizing Data with Excel course available on EdX. To sign up for the course, visit: http://aka.ms/edxexcelbi
Views: 429923 DAT206x
Skills Needed For Data Scientist and Data Analyst
 
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In this Video, We will be discussing about the skills needed for data analyst and data scientist roles. The reason for making one video to discuss both data analyst and data scientist roles is because there are a lot things in common between both these two role. Data Analyst does a lot of descriptive analytics. On the other hand, Data Scientist also does descriptive analytics. But also data scientists do something called predictive analytics. So let's try to understand what Descriptive and Predictive analytics mean. Descriptive Analytics is all about analyzing the historical data to answer this particular question which is "WHAT HAS HAPPENED TILL NOW??". Predictive Analytics also involves analysis of historical data but, predictive analytics is mainly all about answering the question which is.. "WHAT WILL HAPPEN IN THE FUTURE??" Let's understand this with a simple example. I have sales data of XYZ company in a table format. As part of descriptive analytics, we can simply create a scatter chart so that we can quickly understand how the company has been performing in terms of sales in the previous years. Now let's look at predictive analytics. So now that we know how the company has been performing in the previous years, can we predict what's gonna happen to the sales in the coming years?.. Will the sales increase, or decrease or does it remain the same??.. If we are able to answer these questions, then it is called as predictive analytics. So coming back to the comparison of Data Analyst and Data Scientist roles, Now that we have some idea about the differences between the two roles, lets now look at skills needed for each of these two roles. Data Analysts should be good with Math and Statistics. They should be good with handling the data. -- This includes knowledge of ETL (or Extract Transform and Load) operations on data and experience working with popular ETL tools such as Informatica – PowerCenter,IBM – Infosphere Information Server, alteryx, Microsoft – SQL Server Integrated Services (SSIS), Talend Open Studio, SAS – Data Integration Studio ,SAP – BusinessObjects Data Integrator, QlikView Expressor or any other popular ETL tool. -- They should be comfortable in handling data from different sources and in different formats such as text, csv, tsv, excel, json, rdbms and others popular formats. -- They should have excellent knowledge of SQL (or Structured Query Language). Its a Bonus to have -- The knowledge of Big data tools and technologies to handle large data sets. -- NoSQL databases such as HBase, Cassandra and MongoDB. They should be expert in Analysing and Visualizing the data. -- They Should have experience working with popular data analysis and visualization packages in python and R such as numpy, scipy, pandas, matplotlib, ggplot and others. -- Experience with popular data analysis and visualization BI tools such as Tableau, Microsoft Power BI, SAP BI, SAS BI, Oracle BI, QlikView or any other popular BI tool They should have good communication and storytelling skills. Lets now look at the skills needed for data scientist role. Data scientist also does descriptive analytics just like data analysts. Apart from that, they also do predictive analytics. So as part of Descriptive analytics: Data Scientists should be excellent with Math and Statistics. Data scientists should be good with handling data -- So yes, they should have experience working with popular ETL frameworks. -- They should have excellent knowledge of SQL. -- Many companies expect data scientists to have mandatory knowledge of big data tools and technologies to work with large datasets and also to work with structured, semi-structured and unstructured data. -- Its good to have the knowledge of NoSQL databases such as HBase, Cassandra and MongoDB. They should be expert in Analysing and Visualizing the data. -- Experience working with popular data analysis and visualization packages in python and R. -- Experience with popular data analysis and visualization BI tools such as Tableau, Microsoft Power BI, SAP BI, SAS BI, Oracle BI, QlikView or any other popular BI tool. They should also have excellent communication and storytelling skills. And as part of predictive analytics, They should be good in using the techniques in artificial intelligence, data mining, machine learning, and statistical modeling to make future predictions using the historical data. Exposure to popular predictive analytics tools such as SAP Predictive analytics, Minitab, SAS Predictive Analytics, Alteryx Analytics, IBM predictive analytics or any other popular predictive analytics tool. They should have very good exposure to popular machine learning and deep learning packages available for Python and R such as scikit learn, tensorflow, theano,rpart, caret, randomForest, nnet, and other popular libraries.
Views: 58503 Art of Engineer
PHOENIX: Hanford Data Visualization and Analysis Tools
 
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The Department of Energy has partnered with PNNL on PHOENIX, a family of spatially enabled web applications providing quick access to decades of valuable scientific data and insight through intuitive query, visualization and analysis tools. PNNL-Hanford Online ENvironmentalInformation eXchange (PHOENIX) provides a single access point to multiple data sets via standard web browsers. PHOENIX also provides data visualization tools and provides explanations of key data sets to aid understanding. PHOENIX applications are based on the innovative technology applied by PNNL to access and visualize other environmental data sets at the Hanford Site. By integrating previously isolated datasets and developing relevant visualization and analysis tools, PHOENIX applications are enabling DOE to discover new correlations hidden in legacy data, allowing them to more effectively address complex issues at Hanford. Learn more at http://phoenix.pnnl.gov.
Excel Power Query Vs R Tidyverse
 
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https://www.datastrategywithjonathan.com Free YouTube Playlist https://www.youtube.com/playlist?list=PL8ncIDIP_e6vQ0uQofezvKv3yPnL5Unxe From Excel To Big Data and Interactive Dashboard Visualizations in 5 Hours If you use Excel for any type of reporting or analytics then this course is for you. There are a lot of great courses teaching R for statistical analysis and data science that can sometimes make R seem a bit too advanced for every day use. Also since there are many different ways of using R that can often add to the confusion. The reality is that R can be used to make your every day reporting analytics that you do in Excel much faster and easier without requiring any complex statistical techniques while at the same time giving you a solid foundation to expand into those areas if you so wish. This course uses the Tidyverse standards for using R which provides a single, comprehensive and easy to understand method for using R without complicating things via multiple methods. It's designed to build upon the the skills you are already familiar with in Excel to shortcut your learning journey. If you're looking to learn Advanced Excel, Excel VBA or Databases then you need to check out this video series. In this videos series, I will show you how to use Microsoft Excel in different ways that will make you far more effective at working with data. I'm also going to expand your knowledge beyond Excel and show you tips, tricks, and tools from other top data analytics tools such as R Tidyverse, Python, Data Visualisation tools such as Tableau, Qlik View, Qlik Sense, Plotly, AWS Quick Sight and others. We'll start to touch on areas such as big data, machine learning, and cloud computing and see how you can develop your data skills to get involved in these exciting areas. Excel Formulas such as vlookup and sumifs are some of the top reasons for slow spreadsheets. Alternatives for vlookup include power query (Excel 2010 and Excel 2013) which has recently been renamed to Get and Transform in Excel 2016. Large and complex vlookup formulas can be also done very efficiently in R. Using the R Tidyverse libraries you can use the join functions to merge millions of records effortlessly. In comparison to Excel Vlookup, R Tidyverse Join can pull on multiple columns all at the same time. Microsoft Excel Power Query and R Tidyverse Joins are similar to the joins that you do in databases / SQL. The benefit that they have over relational databases such as Microsoft Access, Microsoft SQL Server, MySQL, etc is that they work in memory so they are actually much faster than a database. Also since they are part of an analytics tool instead of a database it is much faster and easier to build your analysis and queries all in the same tools. My very first R Tidyverse program was written to replace a Microsoft Access VBA solution which was becoming complicated and slow. Note that Microsoft Access is very limited in analytics functions and is missing things as simple as Median. Even though I had to learn R programming from scratch and completely re-write the Microsoft Access VBA solution it was so much easier and faster. It blew my mind how much easier R programming with R Tidyverse was than Microsoft Access VBA or Microsoft Excel VBA. If you have any VBA skills or are looking to learn VBA you should definitely checkout my videos on R Tidyverse. To understand why R Tidyverse is so much easier to work with than VBA. R Tidyverse is designed to work directly with your data. So If you want to add a calculated column that’s around one line of script. In Excel VBA, the VBA is used to control the DOM (Document Object Model). In Excel that means that you VBA controls things like cells and sheets. This means your VBA is designed to capture the steps that you would normally do manually in Microsoft Excel or Microsoft Access. VBA is not actually designed to work directly with your data. Note the most efficient path is to reduce the data pulled down from the database in the first place. This is referring to the amount of data you are pulling down from your data warehouse or data lake. It makes no sense to pull data from a data warehouse / data lake to pull into another database to query add joins / lookups to then pull it into Excel or other analysis tool. Often analyst build these intermediate databases because they either don’t have control of the data warehouse or they need to join additional information. All of these operations are done significantly faster in a tool such as R Tidyverse or Microsoft Excel Power Query.
Views: 687 Jonathan Ng
Power Query for EXCEL BI and Reporting
 
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An introduction/overivew to the latest (5th) "Power" tool introduced as part of the Microsoft BI package. Those include PowerPoint, Power Pivot, Power View and Power Map. I've covered those other tools in other Youtubes. Power Query was the missing link in the information management chain. Now we have a full set of robust tools to handle handle the data from start to finish, in a manner that should make everyone happy. Self serve ETL, but with corporate support/control also, when it makes sense. This video covers a simple example using a source xls file as "corporate" data however I've used the tool in much more sophisticated uses, following the same approach. If you can do an easy example it's not much harder to do a more complex product. Power Query is a very easy tool to learn, and use.
Views: 9768 David Wetton
Excel PRO TIP: Power Query Tools | Udemy Instructor, Chris Dutton
 
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In this video, Excel PRO TIP: Power Query Tools by Udemy Instructor, Chris Dutton, you'll explore excel's power query tools. Take the full course on Udemy with the following link: https://www.udemy.com/microsoft-excel-pro-tips-for-power-users/ This course introduces Microsoft Excel's powerful data modeling and business intelligence tools: Power Query, Power Pivot, and Data Analysis Expressions (DAX). If you're looking to become a power Excel user and absolutely supercharge your analytics, this course is the A-Z guide that you're looking for. We'll kick things off by introducing the "Power Excel" landscape, and explore what these tools are all about and why they are changing the world of self-service business intelligence. Using sample data from a fictional supermarket chain, we'll get hands-on with Power Query; a tool to extract, transform, and load data from flat files, folders, databases, API services and more. We'll practice shaping, blending and exploring our project files, and create completely automated loading procedures with only a few clicks. From there we'll dive into Data Modeling 101, and cover the fundamentals of database design and normalization (including table relationships, cardinality, hierarchies and more). We'll take a tour through Excel's data model interface, introduce some best practices and pro tips, and then create our own relational database to analyze throughout the course. Next, we'll use Power Pivot and DAX to explore and analyze our data model. Unlike traditional pivots, Power Pivot allows you to analyze hundreds of millions of rows across multiple data tables, and create supercharged calculated fields using a formula language called Data Analysis Expressions (or "DAX" for short). We'll cover basic DAX syntax, then introduce some of the most powerful and commonly-used functions -- CALCULATE, FILTER, SUMX and more. We'll wrap up the course with a final project, providing an opportunity to practice and apply the tools and techniques covered in the course to a brand new dataset. #Excel #Udemy #ITeachOnUdemy Share your story with #BeAble
Views: 20153 Udemy
E-DAB 02: Data, Proper Data Sets, Excel Tables, Logical Tests, More
 
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Download Start Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-02-Start-DataTablesFilterLogicTest.xlsx Download Finished Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-02-Finished-DataTablesFilterLogicTest.xlsx Pdf notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-02-DataTablesFilterLogicTest.pdf This video #2 in our class teaches about Data, Data Types, Proper Data Sets, Excel Tables, Soring, Filtering and Logical Tests. This class : Data Analysis & Business Intelligence Made Easy with Excel Power Tools - Excel Data Analysis Basics = E-DAB Class – Sponsored by YouTube and taught by Mike Girvin, Highline College Instructor, Microsoft Excel MVP and founder of the excelisfun channel at YouTube. This is a free educational resource for people how want to learn about the Basics of Data Analysis and Business Intelligence using Microsoft Power Tools such as, PivotTables, Power Query, Power Pivot, Power BI Desktop and more. Topics: 1. (00:12) Introduction 2. (01:14) What is Excel? What about the Data in the Cells? 3. (08:30) What is Data, Raw Data? 4. (10:01) Understanding the Difference Between Data & Information. 5. (10:45) Define Proper Data Set. 6. (in pdf notes) Why Proper Data Sets are Mandatory. 7. (14:25) Tables are not Charts 8. (14:50) Use Excel Tables For Dynamic Data. Learn about Excel Table Feature. 9. (20:00) Data Types in Proper Data Sets in Various Tools 10. (24:00) How to Sort Data. 11. (26:07) Filtering & Extracting Data. 12. (28:47) Understand & Use AND Logical Tests and OR Logical Tests 13. (34:35) Summary The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 16480 ExcelIsFun
Create Report in Seconds by Fetching Data from SQL Server using Excel VBA
 
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Create Report in Seconds by Fetching Data from SQL Server using Excel VBA If your manager needs the report very frequently then you need to do the same task again and again. Frankly speaking, I faced this kind of situation in my previous company and I prepared the report using VBA and handed over the file to my manager. Now, whenever he will click the button he will get the report of the LIVE DATA from SQL to Excel. You can read our blog to go through instructions as well as download working and code files, Click here: http://yodalearning.com/tutorials/export-data-from-sql-to-excel-spreadsheet-using-vba/ You can enroll in our Excel VBA course: http://courses.yodalearning.com/p/excel-vba-tutorials CHECK SOME OF THE FREE COURSES WE OFFER http://courses.yodalearning.com/p/free-office-2016-tips Keep yourself updated. Follow us now! http://www.facebook.com/yodalearning http://www.twitter.com/yodalearning
Views: 101872 Yoda Learning Official
OBIEE Training - How to Create an OBIEE 11g Analysis
 
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Read the full OBIEE 11g tutorial here: https://www.fireboxtraining.com/blog/2014/07/07/create-analysis-obiee-11g-tutorial This OBIEE training tutorial demonstrates how to create a simple analysis that uses a sectioned report as well as analysis prompt. We will also apply conditional formatting to highlight certain fields if the revenue value is a certain value or higher. Discover more about learning programming for business at https://www.fireboxtraining.com/
Views: 125428 Firebox Training
Comprehensive Power BI Desktop Example: Visualize Excel Data & Build Dynamic Dashboard (EMT 1360)
 
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Download File: http://people.highline.edu/mgirvin/excelisfun.htm See how to use Power BI Desktop to import, clean and transform Sales Tables from Multiple Excel Files and consolidate into a Single Proper Data Set that can be linked in a Relationship to other tables, and then build DAX Calculated Columns & Measures for Gross Profit that can be used in a Dynamic Dashboard with Map, Column Chart, Line Chart, Card and Slicer visualizations. During the whole process we will compare and contrast how the process is similar and different from Excel’s Power Query and Power Pivot DAX. The steps we will see in this video are: 1. (00:17) Introduction to entire process for Power BI Desktop, including looking at the finished Dashboard 2. (04:50) Import Multiple Excel Files From Folder 3. (05:44) Name Query 4. (06:02) Transform extension column to lowercase 5. (06:34) Filter Files to only include “.xlsx” file extensions 6. (07:05) Remove Columns 7. (07:18) November 2016 Power Query Update Problem 8. (08:05) Add Custom Column with Excel.Workbook Function to extract the Excel Objects from each File. 9. (09:40) Delete Content Column 10. (10:41) Filter to only include Excel Sheet Objects 11. (11:06) Filter to exclude sheets that contain the word “Sheet” 12. (11:40) Remove Columns 13. (11:51) Expand Data and Sheet Name Columns 14. (12:06) Change Field Names 15. (12:22) Change Data Types 16. (14:05) Add Custom Column to calculate Net Revenue Column then round Number.Round function. Then Add Fixed Decimal Data Type. 17. (15:59) Remove columns for Amount and Revenue Discount 18. (16:10) Close and Apply to add to Data Model 19. (17:05) Import Excel Manager Table. Change Data Types to Text. Close and Apply 20. (18:10) Create Relationship between Zip Code Columns 21. (19:03) Create DAX Calculated Column with the IF Function to Categorize Retail Data. Change Data Type. 22. (21:53) Create DAX Measures for: Total Revenue, Total COGS and Gross Profit. Add Currency Number Formatting with No Decimals Showing. 23. (24:28) Create DAX Measures for: Gross Profit Percentage. Add Percentage Number Formatting with Two Decimals Showing. 24. (25:35) Create Map Visualization for Zip Code & Gross Profit Data (Zip Code with relationship to Managers) 25. (26:20) Create Clustered Bar for Manager Names & Gross Profit Data (Zip Code with relationship to Managers) 26. (27:15) Create Clustered Column for Product & Gross Profit Data, with a Line Chart for Gross Profit Percentage 27. (28:19) Create Clustered Column for Payment Method & Gross Profit Data, with a Line Chart for Gross Profit Percentage 28. (28:45) Create Slicer for States. 29. (29:00) Create Card Visualization for Total Revenue, Total COGS, Gross Profit and Gross Profit Percentage. 30. (29:57) Summary Learn Power BI Desktop Basics. Introduction to Power BI Desktop. Getting Started with Power BI Desktop. Create Impactful Reports With Power BI Desktop. Microsoft Power BI.
Views: 137184 ExcelIsFun
Excel Tutorial: What is Business Intelligence and an OLAP Cube? | ExcelCentral.com
 
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This video lesson fully explains the concepts of Business Intelligence, OLAP, MDX and and how they apply to Excel 2013. At http://ExcelCentral.com you can view over 850 free Excel video lessons just like this one. All in full HD with vari-speed and human-transcribed subtitles providing the perfect Excel learning environment. You can also track your progress through the course and print a certificate upon completion. Separate videos are provided for Excel 2007, Excel 2010 and Excel 2013. The lesson begins with an explanation of OLAP and its purpose. You'll learn about OLAP Cubes and how they are divided into Dimensions, Measure and Hierarchies to create a multidimensional data structure. You'll also learn about how the MDX query language is used to extract values from OLAP cubes. This lesson also explains the concept of Business Intelligence and how it applies to OLAP. This video comes from the Data Model, OLAP, MDX and BI session (Session 6 in our Excel 2013 Expert Skills free video training course). This session includes the following video lessons: ▪ Lesson 6-1: Understand primary and foreign keys (11m 27s) http://excelcentral.com/excel2013/expert/lessons/06010-understand-primary-key-foreign-key-relationships.html ▪ Lesson 6-2: Create a simple data model (6m 31s) http://excelcentral.com/excel2013/expert/lessons/06020-create-a-simple-data-model.html ▪ Lesson 6-3: Understand OLAP, MDX and Business Intelligence (10m 17s) http://excelcentral.com/excel2013/expert/lessons/06030-what-is-business-intelligence-and-an-olap-cube.html ▪ Lesson 6-4: Use the GETPIVOTDATA function (4m 31s) http://excelcentral.com/excel2013/expert/lessons/06040-use-the-getpivotdata-function.html ▪ Lesson 6-5: Use the CUBEVALUE function to query an OLAP cube (5m 40s) http://excelcentral.com/excel2013/expert/lessons/06050-use-the-cubevalue-function-to-query-an-olap-cube.html ▪ Lesson 6-6: Convert CUBEVALUE functions to include MDX expressions (5m 48s) http://excelcentral.com/excel2013/expert/lessons/06060-convert-cubevalue-functions-to-include-mdx-expressions.html ▪ Lesson 6-7: Understand OLAP pivot table limitations (10m 52s) http://excelcentral.com/excel2013/expert/lessons/06070-understand-olap-pivot-table-limitations.html ▪ Lesson 6-8: Create an asymmetric OLAP pivot table using Named Sets (4m 57s) http://excelcentral.com/excel2013/expert/lessons/06080-create-an-asymmetric-olap-pivot-table-using-named-sets.html ▪ Lesson 6-9: Understand many-to-many relationships (11m 5s) http://excelcentral.com/excel2013/expert/lessons/06090-understand-many-to-many-relationships.html ▪ Lesson 6-10: Create an OLAP pivot table using a many-to-many relationship (12m 47s) http://excelcentral.com/excel2013/expert/lessons/06100-create-an-olap-pivot-table-using-a-many-to-many-relationship.html You can watch any of the 850 Excel video lessons, free and without any required registration at http://excelcentral.com/excel2013/expert/tutorials/default.html.
Views: 259605 ExcelCentral.com
Basic Excel Business Analytics #30: Excel 2016 Power Query: Data Ribbon Tab, Get and Transform
 
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Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn how to import multiple Text Files (.txt) from a folder into Excel using the new Excel 2016 Power Query: Data Ribbon Tab, Get and Transform group. Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 88884 ExcelIsFun
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1583580 ExcelIsFun
Data Analysis using Excel- Database Queries, Filters and Pivot Tables
 
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I have noticed that many people throughout the world have been interested in my training videos on Using Database Queries and Pivot Tables in Microsoft Excel. So this training video, while very helpful for Active Planner customers, is applicable to any Excel user who wants to create database queries and then analyze that data using Filters and Pivot Tables. And as an added bonus, we will go into SQL Management Studio to build and debug our query and I will show you how to create a PIVOT query. I have created a new video for Sage 300 users so check it out at: https://youtu.be/HXzm8s2mVhI And Sage 500 users check out this new video at: https://youtu.be/UWJ9UrTeEr8 Thank you, Doug Leasure
Views: 172642 ActivePlanner
E-DAB 00: Introduction to Excel Data Analysis & Business Intelligence Class: E-DAB YouTube Class!
 
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Link to full class Playlist at YouTube: https://www.youtube.com/playlist?list=PLrRPvpgDmw0lPPRiJO5dCUratRGpGx3aT Link to full class at Highline Web Site: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/EDAB.htm This video is a short introduction to the : Data Analysis & Business Intelligence Made Easy with Excel Power Tools - Excel Data Analysis Basics = E-DAB Class – Sponsored by YouTube and taught by Mike Girvin, Highline College Instructor, Microsoft Excel MVP and founder of the excelisfun channel at YouTube. This is a free educational resource for people how want to learn about the Basics of Data Analysis and Business Intelligence using Microsoft Power Tools such as, PivotTables, Power Query, Power Pivot, Power BI Desktop and more.
Views: 10165 ExcelIsFun
How to build a query in Toad Data Point
 
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http://quest.com/products/toad-data-point/ In this video, see an overview of how to build a query in the Query Builder tool in Toad Data Point. Some topics include: an overview of the tool bar, how to interact with objects, how to create and analyze joins, how to filter and aggregate queries, and how to view and execute queries.
Views: 10618 Quest
ATLAS ti 8 Windows-The Query Tool
 
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This video explains the Query Tool, including producing written outputs of the results of a query. A detailed explanation of this tool can be found in the Quick Tour manual pages 55-65 (http://atlasti.com/manuals-docs/). 13:44 minutes.
Analyzing And Visualizing Data With Excel 2016
 
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In this workshop, get an introduction to the latest analysis and visualization capabilities in Excel 2016. See how to import data from different sources, create mash/ups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations - from simple to more advanced - can be expressed using DAX, how the result can be visualized and shared.
Views: 34135 Microsoft Power BI
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
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** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ** This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial: 1. What Is The Need For BI? 2. What Is Data Warehousing? 3. Key Terminologies Related To DWH Architecture: a. OLTP Vs OLAP b. ETL c. Data Mart d. Metadata 4. DWH Architecture 5. Demo: Creating A DWH - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Intelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 267209 edureka!
What is OLAP?
 
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This video explores some of OLAP's history, and where this solution might be applicable. We also look at situations where OLAP might not be a fit. Additionally, we investigate an alternative/complement called a Relational Dimensional Model. To Talk with a Specialist go to: http://www.intricity.com/intricity101/ www.intricity.com
Views: 379157 Intricity101
E-DAB 04: PivotTables & Slicers Create Dashboards & Summary Reports
 
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Download Start Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-04-PivotTablesStart.xlsx Download Finished Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-04-PivotTablesFinished.xlsx Pdf notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/EDAB/E-DAB-04-PivotTables.pdf This video teaches all the tricks of PivotTables from Slicers to Show Values As to Dashboards. Learn how to create Cross Tab Repots, Dashboards, Frequency Distributions from Text Data and a CPA Pass Rate Report. This class : Data Analysis & Business Intelligence Made Easy with Excel Power Tools - Excel Data Analysis Basics = E-DAB Class – Sponsored by YouTube and taught by Mike Girvin, Highline College Instructor, Microsoft Excel MVP and founder of the excelisfun channel at YouTube. This is a free educational resource for people how want to learn about the Basics of Data Analysis and Business Intelligence using Microsoft Power Tools such as, PivotTables, Power Query, Power Pivot, Power BI Desktop and more. Topics: 1. (00:12) Introduction 2. (01:35) What is a PivotTable? What is a Cross Tab Report. 3. (03:20) Build a Cross Tab Report with a PivotTable 4. (11:15) PivotTable Cached Data 5. (12:10) Building a Standard PivotTable as Part of Dashboard 6. (12:54) Standard PivotTable vs. Data PivotTable 7. (14:18) What is a Dashboard? 8. (17:20) Use Group By Feature to group Monthly and Yearly Amounts 9. (18:55) Summarize Values By to Change Aggregate Function 10. (19:35) Use Slicers to Filter Entire PivotTable 11. (23:21) Cell Phone Data Examples from Video to Build Frequency Distribution: 12. (24:18) Show Values As to Change to Specific Calculations 13. (25:20) CPA Data Examples from Video to Build CPA Pass Rate Report 14. (27:47) Practice Problems, Homework 15. (27:57) Summary The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 14974 ExcelIsFun
Spatial query , Query Builder , Analysis Tool ,Vector data Classification In Hindi /  हिंदी
 
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This Video is specially for bsc it student Which is doing by mumbai university .. this video contains practical 3,4,5
Views: 2779 Mumbiker Suraj
Tips, Gateway, Embedding and Analysis Services - Roundup #57
 
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There were a bunch of items I found this week. From tips for beginners, to some gateway updates and items for Analysis Services. I have a few bonus links down below that weren't included in the video. Top 10 Tips for Getting Started with Power BI (@ExceleratorBI) http://exceleratorbi.com.au/top-10-tips-getting-started-power-bi/ Translations in Analysis Services 2016 (@marcorus) http://www.sqlbi.com/articles/translations-in-analysis-services-2016/ On-Premises Data Gateway August update https://powerbi.microsoft.com/en-us/blog/on-premises-data-gateway-august-update/ Power BI Embedded GA pricing update https://powerbi.microsoft.com/en-us/blog/power-bi-embedded-ga-pricing-update/ Introducing Tabular Model Explorer for SQL Server Data Tools for Analysis Services Tabular Projects (SSDT Tabular) https://blogs.msdn.microsoft.com/analysisservices/2016/08/16/introducing-tabular-model-explorer-for-sql-server-data-tools-for-analysis-services-tabular-projects-ssdt-tabular/ Bonus: Using The RelativePath And Query Options With Web.Contents() In Power Query And Power BI M Code (@technitrain) https://blog.crossjoin.co.uk/2016/08/16/using-the-relativepath-and-query-options-with-web-contents-in-power-query-and-power-bi-m-code/ SQL Server Migration Assistant for Datazen now generally available https://blogs.msdn.microsoft.com/sqlrsteamblog/2016/08/17/sql-server-migration-assistant-for-datazen-now-generally-available/ Announcing the brand & campaign management solution template for Twitter https://powerbi.microsoft.com/en-us/blog/twitter-solution-template/ Introducing a new Github Repository and PowerShell scripts for Reporting Services https://blogs.msdn.microsoft.com/sqlrsteamblog/2016/08/12/introducing-a-new-github-repository-and-powershell-scripts-for-reporting-services/ LET'S CONNECT! Guy in a Cube -- https://guyinacube.com -- http://twitter.com/guyinacube -- http://www.facebook.com/guyinacube -- Snapchat - guyinacube -- https://www.instagram.com/guyinacube/ ***Gear*** Check out my Tools page - https://guyinacube.com/tools/
Views: 940 Guy in a Cube
Excel PRO TIP: Quick Analysis Tools | Udemy Instructor, Chris Dutton
 
06:14
In this video, Excel PRO TIP: Quick Analysis Tools by Udemy Instructor, Chris Dutton, you'll learn excel analytics tips like outlier detection, monte carlo simulation, forecasting, CUBE functions, etc Take the full course on Udemy with a discount using the following link: https://bit.ly/2TqBKqD What you'll learn: - Build tools to help you automate, streamline, and absolutely revolutionize your workflow with Excel - Explore 75+ unique tips, tools and case studies that you won't find in ANY other course, guaranteed - Get LIFETIME access to resources, Excel project files, quizzes, and 1-on-1 expert support - Master data analysis tools like Goal Seek, Scenario Manager, Solver, and Analysis ToolPak - Practice with fun, interactive, and highly effective lessons from a best-selling Excel instructor - Become an absolute Excel POWER USER #Excel #Udemy #ITeachOnUdemy Share your story with #BeAble
Views: 21533 Udemy
LISA17 - Fast Log Analysis Made Easy by Automatically Parsing Heterogeneous Logs
 
29:33
Biplob Debnath and Will Dennis, NEC Laboratories America, Inc. @bkdebnath Existing log analysis tools like ELK (Elasticsearch-LogStash-Kibana), VMware LogInsight, Loggly, etc. provide platforms for indexing, monitoring, and visualizing logs. Although these tools allow users to relatively easily perform ad-hoc queries and define rules in order to generate alerts, they do not provide automated log parsing support. In particular, most of these systems use regular expressions (regex) to parse log messages. These tools assume that the administrators know how to work with regex, and make the admins manually parse and define the fields of interest. By definition, these tools support only supervised parsing as human input is essential. However, human involvement is clearly non-scalable for heterogeneous and continuously evolving log message formats in systems such as IoT, and it is humanly impossible to manually review the sheer number of log entries generated in an hour, let alone days and weeks. On top of that, writing regex-based parsing rules is long, frustrating, error-prone, and regex rules may conflict with each other especially for IoT-like systems. In this talk, we describe how we automatically generate regex rules based on the log data, which is described further in our research work, LogMine: Fast Pattern Recognition for Log Analytics, published at the CIKM 2016 conference. We also show a demo to illustrate how to integrate our solution with the popular ELK stack. View the full LISA17 program: https://www.usenix.org/lisa17/program
Views: 963 USENIX
MSPTDA 15: Comprehensive Introduction to Excel Power Pivot, DAX Formulas and DAX Functions
 
02:04:00
Download Excel START File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/15Video/015-MSPTDA-ComprehensiveIntroPowerPivot.xlsx Second Excel Start File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/15Video/015-WhyDAXandNotStandardPivotTable.xlsx Download Zipped Folder with Text Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/15Video/015-TextFiles.zip Download Excel FINISHED File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/015-FinishedDashboard-Finished.xlsx Download pdf Notes: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/015-MSPTDA-PowerPivotComprehensiveIntroduction.pdf Assigned Homework: Download Excel File with Instructions for Homework: Start Excel File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/015-MSPTDA-Homework-Start.xlsx Zipped Data Folder: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/015-MSPTDA-HomeworkExcelDataFiles.zip Examples of Finished Homework: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerPivot/015-MSPTDA-Homework-Finished.xlsx This video teaches everything you need to know about Power Pivot, Data Modeling and building DAX Formulas, including all the gotchas that most Introductory videos do not teach you!!! Comprehensive Microsoft Power Tools for Data Analysis Class, BI 348, taught by Mike Girvin, Excel MVP and Highline College Professor. Topics: (00:15) Introduction & Overview of Topics in Two Hour Video 1. (04:36) Standard PivotTable or Data Model PivotTable? 2. (05:51) Excel Power Pivot & Power BI Desktop? 3. (12:31) Power Query to Extract, Transform and Load Data to Data Model – Get data from Text Files, Relational Database and Excel File. 4. (25:47) Build Relationships 5. (27:43) Introduction to DAX Formulas: Measures & Calculated Columns 6. (29:15) DAX Calculated Column using the DAX Functions, RELATED and ROUND 7. (31:20) Row Context: How DAX Calculated Columns are Calculated: Row Context 8. (33:49) We do not want to use Calculated Column results in PivotTable using Implicit Measures 9. (34:05) DAX Measure to add results from Calculated Column, using DAX SUM Function. 10. (35:29) Number Formatting for DAX Measures 11. (36:35) Data Model PivotTable 12. (39:31) Explicit DAX Formulas rather than Implicit DAX Formulas 13. (41:50) Show Implicit Measures 14. (45:00) Filter Context (First Look) How DAX Measures are Calculated 15. (50:14) Drag Columns from Fact Table or Dimension Table? 16. (53:30) Hiding Columns and Tables from Client Tool 17. (55:52) Use Power Query to Refine Data Model 18. (57:54) SUMX Function (Iterator Function). DAX Measure for Revenue using the SUMX Function to simulate Calculated Columns in DAX Measures 19. (01:01:00) Compare and Contrast Calculated Columns & Measures 20. (01:04:26) Why We Need a Date Table. Why we do NOT use the Automatic Grouping Feature for a Data Model PivotTable 21. (01:06:46) Build an Automatic Date Table in Excel Power Pivot. And then build Relationship. 22. (01:11:00) Introduction to Time Intelligence DAX Functions. See TOTALYTD DAX Function 23. (01:13:47) Introduction to CALCULATE Function: Function that can “see” Data Model and can change the Filter Context. (01:18:00) Also see the ALL and DIVIDE DAX Functions. Create formula for “% of Grand Total”. Also learn about (01:21:30) Context Transition and the Hidden CALCULATE on all Measures. 24. (01:27:18) DAX Formula Benefits. 25. (01:28:00) Example of DAX Formula that is easier to author than if we tried to do it with a Standard Pivot Table or Array Formulas 26. (01:31:50) AVERAGEX Function (Iterator Function) to calculate Average Daily Revenue. 27. (01:34:00) Filter Context (Second Look) AVERAGEX Iterator Function 28. (01:36:16) Build Dashboard. Create multiple DAX Formulas. Create Multiple Data Model PivotTables and a Data Model Chart. 29. (01:38:38) Create Measures for Gross Profit and Gross Profit % 30. (01:41:27) Continue making more Data Model PivotTables. 31. (01:41:50) Make Data Model Pivot Chart. 32. (01:45:10) Conditional Formatting for Data Model PivotTable. 33. (01:46:22) DAX Text Formula for title of Dashboard 34. (01:47:50) CUBE Function to Convert Data Model PivotTable to Excel Spreadsheet Formulas. 35. (01:50:05) Adding New Data and Refreshing. 36. (01:50:40) Update Excel Power Pivot Automatic Date (Calendar) Table. Clue is the blank in the Dimension Table Filter. 37. (01:52:20) How to Double Check that a DAX Formula is yielding the correct answer? 38. (01:53:22) DAX Table Functions. See CALCULATETABLE DAX Function. 39. (01:55:07) DAX Studio to visualize DAX Table Functions, and to efficiently create DAX Formulas 40. (02:00:12) Existing Connections to import data from Data Model into an Excel Sheet (02:03:15) Summary
Views: 35751 ExcelIsFun
ATLAS ti Mac - An Overview (Extended Version)
 
02:08:21
In this video, Ricardo Contreras provides an overview of ATLAS.ti Mac. Fundamental tools and procedures. See interactive table of contents below. TABLE OF CONTENTS 0:08 Introduction 3:04 The interface: Top menus 4:14 The interface: Navigator-Accessing documents 5:15 The interface: Navigator-Accessing quotations 6:04 The interface: Navigator-Accessing codes 7:00 The interface: Navigator-Accessing memos 8:14 The interface: Navigator-Accessing networks 11:20 The interface: Navigator-Showing/hiding 11:48 The interface: Inspector 13:51 The interface: Multi-document view 16:12 Creating a new project 16:42 Importing documents to the project 18:50 Writing comments on documents 21:48 Document manager 25:09 Creating an output of the list of documents 30:29 Grouping documents according to shared attributes 34:54 Segmentation: creating quotations and commenting them; creating codes inductively and commenting them 48:03 Quotation manager 50:07 Creating outputs of quotations 53:14 Creating and commenting (i.e., defining) codes 54:25 Coding with codes previously created and codes created inductively 1:00:43 Organizing the code system: prefixes, code groups and colors 1:04:52 Networks 1:10:22 Interrogating the data: queries and their outputs 1:14:15 Memos 1:20:37 Word Cruncher: Counting word frequencies 1:25:40 Code Document Table: Code frequencies 1:29:18 Code co-occurrences 1:43:51 Grouping memos (although shown in relation to co-occurrences, this applies to all memos) 1:44:35 Memo outputs 1:46:03 Review of outputs for all objects of the project 1:51:13 Auto-coding 1:55:43 Hyperlinking (semantic linkages between quotations) 2:00:14 Final words of recommendation: balance fragmentation with integration 2:04:07 Additional learning resources
7 Free Tools to Rank #1 in Google | SEO Optimization Techniques to Skyrocket Your Rankings
 
05:07
You want to rank number one in Google. How do you do it?►►Subscribe here to learn more of my secret SEO tips: https://goo.gl/ScRTwc Find me on Facebook: https://www.facebook.com/neilkpatel/ Read more on my blog: https://neilpatel.com/blog Most people say you need to build links. Most people say you need to do on page SEO. But where do you start? Hey everyone, I'm Neil Patel, and today I'm going to share seven free tools that will help you rank number one on Google. Tip #1: Quick Sprout Analyzer. Quick Sprout's a free tool, go to quicksprout.com, put in your URL, it's a gamified SEO application, and it'll break down the problems, and will walk you through how to fix them step by step. If you're not putting in the right keywords in your title tag or your description or your alt image tags, Quick Sprout will tell you, and Quick Sprout can publish them all for you. This will help with SEO optimization and google ranking. #2: Yoast SEO plugin. It's one of my favorite tools. With the Yoast SEO plugin, every time you publish a blog post, it'll give you a score and tell you, hey, here's how you can optimize every single one of your blog posts to get the maximum amount of traffic. #3: Google Search Console. With Google Search Console every time you publish a new blog post or a page, you have an XML site map. The XML site map is created by the Yoast Plugin which you then submit to Search Console. Search Console shows you how many impressions you're getting, how many clicks you're getting, which pages are popular, and it even shows you which keywords are getting a lot of impressions for, but not a lot of clicks. You can then go and optimize your content by adding those keywords in, adjusting your title tag, your meta description to include those keywords, and maximize your click-through rate and boost your google ranking. #4: Google Trends. Google Trends shows you brand queries. That way you'll know which brands are more popular and what people are searching for. Take the car industry for example. There's General Motors, and BMW. They both have millions of dollars to spend on SEO. They both have millions of back links. How does Google know which to rank higher? One of the factors within Google is brand queries and Google Trends will show you that BMW is searched far more than General Motors. So what's Google going to do? They're going to rank the more popular car manufacturer ahead of the other. #5: websiteresponsivetest.com More people are using Google on their mobile or tablet devices than they are on their desktop or laptops. You want to make sure your website is responsive, and people on mobile devices can load your website extremely fast, and using this free tool, it'll show you how other websites and mobile visitors are seeing your website. #6: Screaming Frog. Screaming Frog is a super technical SEO optimization tool. You put in a URL, and it shows you every little thing that's wrong, from titles to headings to keywords to links. It analyzes every little thing from the super advanced technical framework. #7: Google PageSpeed Insights. Google PageSpeed Insights shows how fast your website loads and if it loads slow, that's okay. They break down a list that shows what you need to improve both for desktop devices and mobile devices, so that way your website can load extremely fast. Make sure your website loads extremely fast. Check out those tools, they work really well, and will help you rank #1 in google. If you want more tools and tips like this, make sure you subscribe to this channel, because I'm going to be releasing more videos soon, that cover more SEO optimization tools that can help boost your Google rankings as well as tips so that way you can climb faster to the top. And if you need help with online or digital marketing leave a question or comment below and I'll be sure to answer!
Views: 317616 Neil Patel
SAP BW tutorials for Begineers
 
01:16:15
http://www.ibmitsolutions.com/sap-bwbi-online-training/ Course: SAP BI 7.0/BW 7.3, ABAP Duration: 50 hours Highlights of our training:  Real time Industry Experienced Trainer.  Interactive Training session using web conferencing tool  Normal track, weekend and fast track classes according to convenience  Student will be provided session recording capability to record each session  We provide Training Material, Exercises and Real Time Examples  Resume preparation and Certification Guidance  We will provide class and demo sessions at student flexible timings.  In training case studies and real time scenarios covered. Introduction to SAP Business Intelligence  SAP Net weaver BI Architecture / BI Platform  Star Schema and Extended Star Schema  Multidimensional modeling  Entity Relationship Modeling  Enterprise Data Modeling  Enterprise Reporting, Query and Analysis  SAP BW vs Other Data warehousing Tools  Data Acquisition / Data Extraction concepts SAP BW Phases  Modeling  Extraction  Reporting Modeling  Info Area ,Info Object Catalogs  Info Objects(Characteristics & Key Figures)  Application Component  Data Source  Transfer Rules  Info Source  Update Rules  Different types of Routines  Info Package  Transformations  Data Transfer Process(DTP)  Error DTP  Metadata Repository BI 7.0 Info Providers  Master Data – Attributes, Texts, Hierarchies  Standard DSO  Write-optimized DSO  Direct Update DSO  Standard Info Cube  Virtual Providers  InfoSet  MultiProvider  Aggregation Level  Others  Open Hub Destination  Analysis Process designer BW 7.3 Info Providers  SAP NetWeaver BW 7.3 Features Overview  Graphical Data Modeling  Graphical Data Flow Modeling Basics  Data Flow Copying  Data Flow Generation  Data Flow Migration  Advanced InfoProviders  Semantically Partitioned Object (SPO)  Hybrid InfoProviders  Transient Providers  The New BW 7.3 Hierarchy ETL Business Content  Importance of Business Content  Business Content Installation & Activation  Business Content Data Source, DSO’s, Cubes, Reports, etc… Data Acquisition / Data Extraction  Flat file Extraction  Business Content Extractions using MD/TD SD,MM and FI  Logistics Extraction  Generic Data Extraction using MD/TD Tables  Delta mechanism  CO-PA Extraction  FI-SL Extraction  Data source Enhancement Process Chains  Process Chains, Process Types  Scheduling  Monitor (Header, Status, Details)  Real time scenarios from support projects Transport Mechanism  Review of system Landscape  Collecting Objects  Creating Transports  Releasing Transport  Importing and Monitoring Transport Reporting  Introduction of Various Reporting Tools Functional Overview of Business Explorer Query Designer  Introduction of BEx Query  Reusable Query Elements  Filters, Columns & Rows  Characteristic Restrictions & Free Characteristics  Formulas & Calculated Key Figures  Restricted Keyfigures and Variables with Texts  Report to Report Interface or Jump Starts  Query Extracts using RSCRM_BAPI  Exceptions, Conditions, Structures, Cell Definitions and others Business Explorer Analyzer  Introduction to BEx Analyzer  Filtering Option  Properties available in Analyzer Performance Improvement  Aggregates  Compression  Re-Modeling  Re- Partitioning  Indexes and DB Statistics  Number Range Buffering  Read Mode & OLAP cache  Line Item Dimension & High Cardinality  Read Mode & OLAP cache  Business Warehouse Accelerator  Others Types of Projects  Real Time Implementation Projects  Up-Gradation project  Enhancements to the existing Implementation project  Support projects Introduction to SAP ABAP  What is SAP  SAP Architecture and where ABAP fits in  ABAP Development Workbench Tools  Object Navigator  Workbench Organizer  Data Dictionary ABAP Dictionary  Tables  Views  Lock Objects ABAP Programming Techniques  Reports Statement  Line Size  Line-count  Message  Page Heading  Report Comment Section  Declarations  Tables  Includes  Variables (Data Types and Data Objects)  Structures  Internal Table  Constants ABAP for SAP BI Consultant:  Field level Routine  Start Routine  End Routine  Expert Routine  Infopackage level Routine  DataSource Enhancements Thanks !!!!!!
Basic Excel Business Analytics #27: Clean & Transform Data: Formulas, Flash Fill, Power Query, TTC
 
29:49
Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn about how to clean and transform data to prepare it for data analysis using Formulas, Flash Fill, Power Query and Text To Columns: 1) (00:19) Intro to Import, Clean and Transform Data for this section of the class 2) (02:00) Use VLOOKUP to create better labels for our data set and for our PivotTable Report with % of Column Totals and a Slicer (Filter) 3) (05:40) Get rid of extra spaces with the TRIM Function 4) (07:11) Get rid of extra spaces with Flash Fill 5) (09:08) Formula: Convert ISO Dates like 20140212 (Year, Month, Day) to Serial Number Dates. TEXT function, Custom Number Format “0000-00-00” and add zero (any math operation) to convert number stroed as text back to a number. 6) (11:14) Text To Column: Convert ISO Dates like 20140212 (Year, Month, Day) to Serial Number Dates. 7) (12:12) Power Query: Convert ISO Dates like 20140212 (Year, Month, Day) to Serial Number Dates. 8) (15:16) Formula: Split Region and City from Same Cell. LEFT and SEARCH functions. 9) (17:19) Flash Fill: Split Region and City from Same Cell. 10) (17:44) Text To Columns: Split Region and City from Same Cell. 11) (18:43) Formulas: Get Date and Sales from a transaction description in a single cell. See the MID, SUBSTITUTE, SEARCH and REPLACE functions. 12) (23:53) Power Query: Get Department, Product, Date and Sales from a transaction description in a single cell. 13) (27:35) Compare the dynamic (ability to update when source data changes) aspects of Formulas and Power Query. 14) (28:27) Summary and Conclusion Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 31094 ExcelIsFun
SAP BIBW ECC Extraction training class
 
01:23:01
http://www.ibmitsolutions.com/sap-bwbi-online-training/ Course: SAP BI 7.0/BW 7.3, ABAP Duration: 50 hours Highlights of our training:  Real time Industry Experienced Trainer.  Interactive Training session using web conferencing tool  Normal track, weekend and fast track classes according to convenience  Student will be provided session recording capability to record each session  We provide Training Material, Exercises and Real Time Examples  Resume preparation and Certification Guidance  We will provide class and demo sessions at student flexible timings.  In training case studies and real time scenarios covered. Introduction to SAP Business Intelligence  SAP Net weaver BI Architecture / BI Platform  Star Schema and Extended Star Schema  Multidimensional modeling  Entity Relationship Modeling  Enterprise Data Modeling  Enterprise Reporting, Query and Analysis  SAP BW vs Other Data warehousing Tools  Data Acquisition / Data Extraction concepts SAP BW Phases  Modeling  Extraction  Reporting Modeling  Info Area ,Info Object Catalogs  Info Objects(Characteristics & Key Figures)  Application Component  Data Source  Transfer Rules  Info Source  Update Rules  Different types of Routines  Info Package  Transformations  Data Transfer Process(DTP)  Error DTP  Metadata Repository BI 7.0 Info Providers  Master Data – Attributes, Texts, Hierarchies  Standard DSO  Write-optimized DSO  Direct Update DSO  Standard Info Cube  Virtual Providers  InfoSet  MultiProvider  Aggregation Level  Others  Open Hub Destination  Analysis Process designer BW 7.3 Info Providers  SAP NetWeaver BW 7.3 Features Overview  Graphical Data Modeling  Graphical Data Flow Modeling Basics  Data Flow Copying  Data Flow Generation  Data Flow Migration  Advanced InfoProviders  Semantically Partitioned Object (SPO)  Hybrid InfoProviders  Transient Providers  The New BW 7.3 Hierarchy ETL Business Content  Importance of Business Content  Business Content Installation & Activation  Business Content Data Source, DSO’s, Cubes, Reports, etc… Data Acquisition / Data Extraction  Flat file Extraction  Business Content Extractions using MD/TD SD,MM and FI  Logistics Extraction  Generic Data Extraction using MD/TD Tables  Delta mechanism  CO-PA Extraction  FI-SL Extraction  Data source Enhancement Process Chains  Process Chains, Process Types  Scheduling  Monitor (Header, Status, Details)  Real time scenarios from support projects Transport Mechanism  Review of system Landscape  Collecting Objects  Creating Transports  Releasing Transport  Importing and Monitoring Transport Reporting  Introduction of Various Reporting Tools Functional Overview of Business Explorer Query Designer  Introduction of BEx Query  Reusable Query Elements  Filters, Columns & Rows  Characteristic Restrictions & Free Characteristics  Formulas & Calculated Key Figures  Restricted Keyfigures and Variables with Texts  Report to Report Interface or Jump Starts  Query Extracts using RSCRM_BAPI  Exceptions, Conditions, Structures, Cell Definitions and others Business Explorer Analyzer  Introduction to BEx Analyzer  Filtering Option  Properties available in Analyzer Performance Improvement  Aggregates  Compression  Re-Modeling  Re- Partitioning  Indexes and DB Statistics  Number Range Buffering  Read Mode & OLAP cache  Line Item Dimension & High Cardinality  Read Mode & OLAP cache  Business Warehouse Accelerator  Others Types of Projects  Real Time Implementation Projects  Up-Gradation project  Enhancements to the existing Implementation project  Support projects Introduction to SAP ABAP  What is SAP  SAP Architecture and where ABAP fits in  ABAP Development Workbench Tools  Object Navigator  Workbench Organizer  Data Dictionary ABAP Dictionary  Tables  Views  Lock Objects ABAP Programming Techniques  Reports Statement  Line Size  Line-count  Message  Page Heading  Report Comment Section  Declarations  Tables  Includes  Variables (Data Types and Data Objects)  Structures  Internal Table  Constants ABAP for SAP BI Consultant:  Field level Routine  Start Routine  End Routine  Expert Routine  Infopackage level Routine  DataSource Enhancements Thanks !!!!!!
Introduction to Text Analysis with NVivo 11 for Windows
 
40:02
It’s easy to get lost in a lot of text-based data. NVivo is qualitative data analysis software that provides structure to text, helping you quickly unlock insights and make something beautiful to share. http://www.qsrinternational.com
Views: 147177 NVivo by QSR
Google I/O 2013 - Google Analytics and AdSense Data Analysis in BigQuery
 
33:43
Balachandar Krishnamoorthy, Clancy Childs, Duncan Mckie, Louis Collard Google Analytics and AdSense are two Google products that will soon be able to deliver their reporting data into BigQuery, Google's big data query and analysis engine. In this session, see how Google Analytics Premium and AdSense users are able to conduct advanced data analysis using BigQuery. For all I/O 2013 sessions, go to https://developers.google.com/live
Views: 7629 Google Developers
MSPTDA 03: Power Query Introduction: Importing & Transformation Data in Excel & Power BI Desktop
 
57:13
Download Excel START File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/003-MSPTDA-IntroToPowerQueryStartFile.xlsx Download Access START File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-AccessData.accdb Download zipped folder with Text Files: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-TextFiles.zip Download Excel FINISHED File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/003-MSPTDA-IntroToPowerQueryFinishedFile.xlsx Download Power BI FINISHED File: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-PowerBITextImportFinished.pbix Download pdf Notes about Power Query: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/003-MSPTDA-IntroToPowerQuery.pdf Buy excelisfun products: https://teespring.com/stores/excelisfun-store In this Video learn all about Power Query. A complete Introduction to all aspects of Power Query. Topics: 1. (00:12) Introduction 2. (02:26) Example 1: Clean and Transform Data in Excel. Look at Excel Power Query User Interface & M Code. Look at Locations to Load Data. Edit, Delete and Add Steps to Power Query Solution. Add new data and Refresh Report and Power Query Transformation. 3. (27:20) Example 2: Extract & Import, Clean & Transform and Load Data from Relational Access Database into Excel Power Pivot Data Model and create Star Schema. 4. (40:37) Example 3: Extract & Import, Clean & Transform and Load Data From Multiple Text Files into Power BI Desktop Data Model. We will Combine all Text Files into Single Table. 5. (52:54) Example 4: Replace Complex Excel Array Formulas with Simple Power Query Solution. See how to Extract a Sorted Unique List. 6. (55:50) Summary Comprehensive Microsoft Power Tools for Data Analysis Class, BI 348, taught by Mike Girvin, Excel MVP and Highline College Professor. Assigned Homework: Download Word Document and read: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-HomeworkDescription.docx Then download the rest of the files and complete the homework: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-ImportTextFilesForHomework.zip Examples of Finished Homework: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-FinishedHomework.xlsx https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/PowerQuery/MSPTDA-003-FinishedHomework.pbix The Power Query logo used in this video is copyright of and used with the express permission of https://powerquery.training Thanks to Ken Puls and Miguel Escobar for letting me use their logo!!!!
Views: 42730 ExcelIsFun
"I See What You Mean" by Peter Alvaro
 
52:29
I love query languages for many reasons, but mostly because of their semantics. Wait, come back! In contrast to most systems programming languages (whose semantics can be quite esoteric), the semantics of a query (given some inputs) are precisely its outcome -- rows in tables. Hence when we write a query, we directly engage with its semantics: we simply say what we mean. This makes it easy and natural to reason about whether our queries are correct: that is, whether they mean what we intended them to mean. Query languages have traditionally been applied to a relatively narrow domains: historically, data at rest in data stores; more recently, data in motion through continuous, "streaming" query frameworks. Why stop here? Could query languages do for a notoriously complex domain such as distributed systems programming what they have done so successfully for data management? How would they need to evolve to become expressive enough to capture the programs that we need to write, while retaining a simple enough semantics to allow mere mortals to reason about their correctness? I will attempt to answer these questions (and raise many others) by describing a query language for distributed programming called Dedalus. Like traditional query languages, Dedalus abstracts away many of the details we typically associate with programming, making data and time first-class citizens and relegating computation to a subordinate role, characterizing how data is allowed to change as it moves through space and time. As we will see, this shift allows programmers to directly reason about distributed correctness properties such as consistency and fault-tolerance, and lays the foundations for powerful program analysis and repair tools (such as Blazes and LDFI), as well as successive generations of data-centric programming languages (including Bloom, Edelweiss and Eve). Peter Alvaro UNIVERSITY OF CALIFORNIA SANTA CRUZ @palvaro Peter Alvaro is an Assistant Professor of Computer Science at the University of California Santa Cruz. His research focuses on using data-centric languages and analysis techniques to build and reason about data-intensive distributed systems, in order to make them scalable, predictable and robust to the failures and nondeterminism endemic to large-scale distribution. Peter is the creator of the Dedalus language and co-creator of the Bloom language. While pursuing his PhD at while UC Berkeley, Peter co-developed and taught Programming the Cloud, an undergraduate course that explored distributed systems concepts through the lens of software development. Prior to attending Berkeley, Peter worked as a Senior Software Engineer in the data analytics team at Ask.com. Peter's principal research interests are databases, distributed systems and programming languages.
Views: 36272 Strange Loop
SimpleOpinions -  Data Tools Query Tutorial
 
01:59
How to use query tool to analyze your survey data
Views: 14 SimpleOpinions
Excel 2013 Statistical Analysis #2: Install Data Analysis Add-in For Amazing Excel Statistical Tools
 
01:15
Download files: http://people.highline.edu/mgirvin/excelisfun.htm Install Data Analysis Add-in For Amazing Excel Statistical Tools in Excel 2013.
Views: 38252 ExcelIsFun