Mastering Microsoft Power BI :: 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 int...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham :
Packt Publishing,
2018.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | DAX variables. |
| Beschreibung: | 1 online resource (632 pages) |
| ISBN: | 9781788292283 1788292286 1788297237 9781788297233 |
Internformat
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| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 500 | |a DAX variables. | ||
| 520 | |a 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. | ||
| 650 | 0 | |a Information visualization. |0 http://id.loc.gov/authorities/subjects/sh2002000243 | |
| 650 | 6 | |a Visualisation de l'information. | |
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| 776 | 0 | 8 | |i Print version: |a Powell, Brett. |t Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |d Birmingham : Packt Publishing, ©2018 |
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| contents | 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. |
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| publisher | Packt Publishing, |
| record_format | marc |
| spelling | Powell, Brett. Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. Birmingham : Packt Publishing, 2018. 1 online resource (632 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Print version record. 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. DAX variables. 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. Information visualization. http://id.loc.gov/authorities/subjects/sh2002000243 Visualisation de l'information. Operational research. bicssc Enterprise software. bicssc Information visualization. bicssc Computers Enterprise Applications General. bisacsh Computers Enterprise Applications Business Intelligence Tools. bisacsh REFERENCE Questions & Answers. bisacsh Information visualization fast has work: Mastering Microsoft Power BI (Work) https://id.oclc.org/worldcat/entity/E39PCXJGkr38fv4GcFmVxvHtJC https://id.oclc.org/worldcat/ontology/hasWork Print version: Powell, Brett. Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. Birmingham : Packt Publishing, ©2018 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1775076 Volltext |
| spellingShingle | Powell, Brett Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. 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. Information visualization. http://id.loc.gov/authorities/subjects/sh2002000243 Visualisation de l'information. Operational research. bicssc Enterprise software. bicssc Information visualization. bicssc Computers Enterprise Applications General. bisacsh Computers Enterprise Applications Business Intelligence Tools. bisacsh REFERENCE Questions & Answers. bisacsh Information visualization fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2002000243 |
| title | Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |
| title_auth | Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |
| title_exact_search | Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |
| title_full | Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |
| title_fullStr | Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |
| title_full_unstemmed | Mastering Microsoft Power BI : Expert techniques for effective data analytics and business intelligence. |
| title_short | Mastering Microsoft Power BI : |
| title_sort | mastering microsoft power bi expert techniques for effective data analytics and business intelligence |
| title_sub | Expert techniques for effective data analytics and business intelligence. |
| topic | Information visualization. http://id.loc.gov/authorities/subjects/sh2002000243 Visualisation de l'information. Operational research. bicssc Enterprise software. bicssc Information visualization. bicssc Computers Enterprise Applications General. bisacsh Computers Enterprise Applications Business Intelligence Tools. bisacsh REFERENCE Questions & Answers. bisacsh Information visualization fast |
| topic_facet | Information visualization. Visualisation de l'information. Operational research. Enterprise software. Computers Enterprise Applications General. Computers Enterprise Applications Business Intelligence Tools. REFERENCE Questions & Answers. Information visualization |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1775076 |
| work_keys_str_mv | AT powellbrett masteringmicrosoftpowerbiexperttechniquesforeffectivedataanalyticsandbusinessintelligence |