http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
a practical guide to self-service data analytics with Excel 2016 and Power BI desktop
Practical guide to self-service data analytics with Excel 2016 and Power BI desktop
1 online resource (xvii, 348 pages) : color illustrations
Analyze your company's data quickly and easily using Microsoft's latest tools. Build scalable and robust data models to work from. Learn to clean and combine different data sources effectively. Create compelling visualizations and share them with your colleagues. Author Dan Clark takes you through each topic using step-by-step activities and plenty of screen shots to help familiarize you with the tools. This second edition includes new material on advanced uses of Power Query, along with the latest user guidance on the evolving Power BI platform. Beginning Power BI is your hands-on guide to quick, reliable, and valuable data insight. What You Will Learn: Simplify data discovery, association, and cleansing Create solid analytical data models Create robust interactive data presentations Combine analytical and geographic data in map-based visualizations Publish and share dashboards and reports.
At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Part I: Building Models in Power Pivot; Chapter 1: Introducing Power Pivot; Why Use Power Pivot?; The xVelocity In-memory Analytics Engine; Enabling Power Pivot for Excel; Exploring the Data Model Manager Interface; Summary; Chapter 2: Importing Data into Power Pivot; Importing Data from Relational Databases; Importing Data from Text Files; Importing Data from a Data Feed; Importing Data from an OLAP Cube; Reusing Existing Connections to Update the Model; Summary.
Chapter 3: Data Munging with Power QueryDiscovering and Importing Data; Transforming, Cleansing, and Filtering Data; Merging and Shaping Data; Grouping and Aggregating Data; Inserting Calculated Columns; Summary; Chapter 4: Creating the Data Model; What Is a Data Model?; Creating Table Relations; Creating a Star Schema; Understanding When to Denormalize the Data; Creating Linked Tables; Creating Hierarchies; Making a User-Friendly Model; Summary; Chapter 5: Creating Calculations with DAX; What Is DAX?; Implementing DAX Operators; Working with Text Functions; Using DAX Date and Time Functions.
Using Informational and Logical FunctionsGetting Data from Related Tables; Using Math, Trig, and Statistical Functions; Tips for Creating Calculations in Power Pivot; Summary; Chapter 6: Creating Measures with DAX; Measures vs. Attributes; Creating Common Aggregates; Mastering Data Context; Altering the Query Context; Using Filter Functions; Creating KPIs; Summary; Chapter 7: Incorporating Time Intelligence; Date-Based Analysis; Creating a Date Table; Time Period-Based Evaluations; Shifting the Date Context; Using Single Date Functions; Creating Semi-Additive Measures; Summary.
Chapter 8: Data Analysis with Pivot Tables and ChartsPivot Table Fundamentals; Slicing the Data; Adding Visualizations to a Pivot Table; Working with Pivot Charts ; Using Multiple Charts and Tables; Using Cube Functions ; Summary; Part II: Building Interactive Reports and Dashboards with Power BI Desktop; Chapter 9: Introducing Power BI Desktop; Setting Up the Power BI Environment; Getting, Cleaning, and Shaping Data; Creating Table Relationships; Adding Calculations and Measures; Incorporating Time-based Analysis; Summary; Chapter 10: Creating Reports with Power BI Desktop.
Creating Tables and MatricesConstructing Bar, Column, and Pie Charts; Building Line and Scatter Charts; Creating Map-Based Visualizations; Linking Visualizations in Power BI; Drilling Through Visualizations; Summary; Chapter 11: Publishing Reports and Creating Dashboards in the Power BI Portal; Creating a User-Friendly Model; Publishing Power BI Desktop Files to the Power BI Service; Adding Tiles to a Dashboard; Sharing Dashboards; Refreshing Data in Published Reports; Summary; Chapter 12: Creating a Complete Solution; Use Case 1: Reseller Sales Analysis; Load the Data; Create the Model.
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Beginning Power BI : A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop