http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Expert techniques for effective data analytics and business intelligence
This book will show you how to use Power BI effectively to create a variety of visualizations and BI dashboards. Right from gathering data through various data sources, you will learn to perform effective visual analytics. By the end of this book, you will be able to gain unique, hidden insights into your data using Microsoft Power BI.
Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Planning Power BI Projects; Power BI deployment modes; Corporate BI; Self-Service Visualization; Self-Service BI; Choosing a deployment mode; Project discovery and ingestion; Sample Power BI project template ; Sample template -- Adventure Works BI; Power BI project roles; Dataset designer; Report authors; Power BI admin; Project role collaboration; Power BI licenses; Power BI license scenarios; Power BI Premium features; Data warehouse bus matrix; Dataset design process.
Selecting the business processDeclaring the grain; Identifying the dimensions; Defining the facts; Data profiling; Dataset planning; Data transformations; Import versus DirectQuery; Import mode ; DirectQuery mode; Sample project analysis; Summary; Chapter 2: Connecting to Sources and Transforming Data with M; Query design per dataset mode; Import mode dataset queries; DirectQuery dataset queries; Data sources; Authentication; Data source settings; Privacy levels; Power BI as a data source; Power BI Desktop options; Global options; CURRENT FILE options; SQL views; SQL views versus M queries.
SQL view examplesDate dimension view; Mark As Date Table; Product Dimension view; Slowly-changing dimensions; M queries; Data Source Parameters; Staging Queries; DirectQuery staging; Fact and dimension queries; Source Reference Only; M query summary; Excel workbook -- Annual Sales Plan; Data types; Item access in M; DirectQuery report execution; Bridge Tables Queries; Parameter Tables; Security Tables; Query folding; Partial query folding; M Query examples; Trailing three years filter; Customer history column; Derived column data types; Product dimension integration; R script transformation.
M editing toolsAdvanced Editor; Visual Studio Code; Visual Studio; Summary; Chapter 3: Designing Import and DirectQuery Data Models; Dataset layers; Dataset objectives; Competing objectives; External factors; The Data Model ; The Relationships View; The Data View; The Report View; Fact tables; Fact table columns; Fact column data types; Fact-to-dimension relationships; Dimension tables; Hierarchies; Custom sort; Bridge tables; Parameter tables; Measure groups; Last refreshed date; Measure support logic; Relationships; Uniqueness ; Ambiguity; Single-direction relationships; Direct flights only.
Bidirectional relationshipsShared dimensions; Date dimensions ; The CROSSFILTER function; Model metadata; Visibility; Column metadata; Default Summarization; Data format; Data category; Field descriptions; Optimizing performance; Import; Columnar compression; Memory analysis via DMVs; DirectQuery ; Optimized DAX functions; Columnstore and HTAP; Summary; Chapter 4: Developing DAX Measures and Security Roles; DAX measures; Filter context; SQL equivalent; Measure evaluation process; Row context; Scalar and table functions; The CALCULATE() function; Related tables; The FILTER() function.
Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence