Mastering Microsoft Power BI: Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing, Limited
2022
|
| Ausgabe: | 2nd ed |
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (712 Seiten) |
| ISBN: | 9781801818193 |
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| 245 | 1 | 0 | |a Mastering Microsoft Power BI |b Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
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| 505 | 8 | |a Cover -- CopyRight Page -- 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 administrator -- Project role collaboration -- Power BI licenses -- Shared capacity -- Free -- Pro -- Dedicated capacity -- Premium -- Premium Per User -- Embedded -- Power BI license scenarios -- Dataset design -- Data warehouse bus matrix -- Dataset design process -- Select the business process -- Declare the grain -- Identify the dimensions -- Define the facts -- Data profiling -- Data profiling with Power BI Desktop -- Dataset planning -- Data transformations -- Import, DirectQuery, Live, and Composite datasets -- Import mode -- DirectQuery/Live mode -- Composite mode -- Sample project analysis -- Summary -- Chapter 2: Preparing Data Sources -- Query folding -- Partial query folding -- Query design per dataset mode -- Import mode dataset queries -- DirectQuery dataset queries -- DirectQuery report execution -- Composite datasets -- Table storage modes -- 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 examples -- Date dimension view -- Mark as date table -- Product dimension view -- Slowly changing dimensions -- Summary -- Chapter 3: Connecting to Sources and Transforming Data with M -- Types of Power Query M queries -- Organizing queries -- Data source parameters -- Staging queries -- DirectQuery staging -- Fact and dimension queries | |
| 505 | 8 | |a Source reference only -- Excel workbook - Annual Sales Plan -- Parameter tables queries -- Security table queries -- Custom function queries -- Creating Power Query M queries -- Numeric data types -- Item access in M -- Power Query M query examples -- Trailing three years filter -- Combining queries -- Incremental refresh for fact tables -- Customer history column -- Product dimension integration -- R and Python script transformation -- Dataflows -- Power BI Premium dataflow features -- Power Query M editing tools -- Advanced Editor -- Visual Studio Code -- Visual Studio -- Summary -- Chapter 4: Designing Import, DirectQuery, and Composite Data Models -- Dataset layers -- Power BI as a superset of Azure Analysis Services -- Dataset objectives -- Competing objectives -- External factors -- The Data Model -- The Model 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 -- Parameter tables -- Measure groups -- Last refreshed date -- Measure support logic -- Display folders -- Relationships -- Uniqueness -- Ambiguity -- Single-direction relationships -- Direct flights only -- Bidirectional relationships -- Shared dimensions -- Date dimensions -- The CROSSFILTER function -- Model metadata -- Visibility -- Column and measure metadata -- Default summarization -- Data format -- Data category -- Description -- Optimizing data model performance -- Import -- Query caching -- Columnar compression -- Memory analysis via DMVs and the VertiPaq Analyzer -- DirectQuery -- Columnstore and HTAP -- Automatic aggregations -- Composite -- Aggregation tables -- Summary -- Chapter 5: Developing DAX Measures and Security Roles -- DAX measure basics -- Filter context -- SQL equivalent -- Measure evaluation process -- Row context | |
| 505 | 8 | |a Scalar and table functions -- Related tables -- The CALCULATE() function -- The FILTER() function -- DAX variables -- Base measures -- Measure support expressions -- KPI targets -- Current and prior periods -- Date intelligence metrics -- Current versus prior and growth rates -- Rolling periods -- Calculation groups -- Dimension metrics -- Missing dimensions -- Ranking metrics -- Dynamic ranking measures -- Security roles -- Dynamic row-level security -- Performance testing -- Performance analyzer -- DAX Studio -- Summary -- Chapter 6: Planning Power BI Reports -- Report planning process -- Identify the audience -- Define the business questions to answer -- Confirm that the dataset supports the business questions -- Determine interactivity -- Define access and distribution -- Sketch the report layout -- Report architecture diagram -- Visualization best practices -- Choosing the right visual -- Tables and matrices versus charts -- Chart selection -- Visualization anti-patterns -- Visual interactions -- Editing interactions -- Drillthrough report pages -- Custom labels and the back button -- Multi-column drillthrough -- Report filter scopes -- Report filter conditions -- Report and page filters -- Relative date filtering -- Visual-level filtering -- Top N visual-level filters -- Bookmarks -- Selection pane and the Spotlight property -- Custom report navigation -- View mode -- Live connections to Power BI datasets -- Customizing Live connection reports -- Switching Live source datasets -- Switching between import mode and Live mode datasets -- Report design summary -- Summary -- Chapter 7: Creating and Formatting Visualizations -- The Visualizations pane -- Slicers -- Slicer synchronization -- Custom slicer parameters -- What-if parameters -- Page filter or slicer? -- Single-value visuals -- The Card visual -- The KPI visual -- Gauge visual | |
| 505 | 8 | |a Map visuals -- Bubble map -- Filled map -- Waterfall chart -- Power Platform visuals -- Power Apps for Power BI -- Power Automate for Power BI -- Premium visuals -- Scorecard -- Paginated reports -- Elements -- Formatting visualizations -- Tooltips -- Report page tooltips -- Column and line charts -- Column and line chart conditional formatting -- Table and matrix visuals -- Custom format strings -- Table and matrix conditional formatting -- Sparklines -- Values as rows -- Scatter charts -- Summary -- Chapter 8: Applying Advanced Analytics -- AI visuals -- Key influencers -- Decomposition tree -- Q& -- A -- Smart narrative -- R and Python visuals -- R visual -- Python visual -- ArcGIS Maps for Power BI -- Custom visuals -- Adding a custom visual -- Animation and data storytelling -- Play axis for Scatter charts -- Pulse chart -- Analytics pane -- Trend line -- Forecasting -- Quick insights/Analyze -- Explain the increase/decrease -- Mobile-optimized report pages -- Summary -- Chapter 9: Designing Dashboards -- Dashboards versus reports -- Dashboard design -- Visual selection -- Layout -- Navigation pane -- Fullscreen mode -- Supporting tiles -- Dashboard architectures -- Single-dashboard architecture -- Multiple-dashboard architecture -- Organizational dashboard architecture -- Multiple datasets -- Dashboard tiles -- Tile details and custom links -- Real-time data tiles -- Dashboard themes -- Paginated reports -- Excel workbooks -- Live report pages -- Mobile-optimized dashboards -- Summary -- Chapter 10: Managing Workspaces and Content -- Workspaces -- Workspace roles and rights -- Viewer role -- Contributor role -- Member role -- Admin role -- Datasets across workspaces -- My workspace -- Staged deployments -- Workspace datasets -- Power BI REST API and PowerShell module -- Power BI REST API -- Power BI PowerShell module | |
| 505 | 8 | |a Workspace and content identifiers -- PowerShell sample scripts -- Power BI deployment pipelines -- Content sensitivity and protection -- Information protection -- Data loss prevention -- Version control -- OneDrive for Business -- Source control for M and DAX code -- MSHGQM -- Metadata management -- Field descriptions -- Creating descriptions -- View field descriptions -- Metadata Mechanic -- Metadata reporting -- Standard metadata reports -- Server and database parameters -- Querying the DMVs from Power BI -- Integrating and enhancing DMV data -- Metadata report pages -- Summary -- Chapter 11: Managing the On-Premises Data Gateway -- On-premises data gateway planning -- Top gateway planning tasks -- Determining whether a gateway is needed -- Identifying where the gateway should be installed -- Defining the gateway infrastructure and hardware requirements -- Defining gateway roles and permissions -- Planning for recovery keys -- Standard versus personal mode -- Gateway concepts -- Gateway clusters -- Gateway architectures -- Gateway security -- Gateway installation and configuration -- The gateway service account -- TCP versus HTTPS mode -- Connectors -- Recovery Keys -- Managing gateway clusters -- Gateway administrators -- Gateway data sources and users -- PowerShell support for gateway clusters -- Troubleshooting and monitoring gateways -- Restoring, migrating, and taking over a gateway -- Gateway diagnostics -- Gateway monitoring reports -- Data refresh -- Scheduled data refresh -- DirectQuery datasets -- Live connections to Analysis Services models -- Dashboard cache refresh -- Summary -- Chapter 12: Deploying Paginated Reports -- Paginated reports in the Power BI service -- Planning paginated reports -- Building and publishing paginated reports -- Identifying and interacting with paginated reports | |
| 505 | 8 | |a Printing, exporting, subscribing, and sharing | |
| 650 | 4 | |a Microsoft Power BI (Computer file) | |
| 650 | 4 | |a Business-Data processing | |
| 650 | 4 | |a Visual analytics | |
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| 700 | 1 | |a Gordon, Leon |e Sonstige |4 oth | |
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Datensatz im Suchindex
| _version_ | 1804184932479664129 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Deckler, Greg |
| author_facet | Deckler, Greg |
| author_role | aut |
| author_sort | Deckler, Greg |
| author_variant | g d gd |
| building | Verbundindex |
| bvnumber | BV048831058 |
| collection | ZDB-30-PQE |
| contents | Cover -- CopyRight Page -- 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 administrator -- Project role collaboration -- Power BI licenses -- Shared capacity -- Free -- Pro -- Dedicated capacity -- Premium -- Premium Per User -- Embedded -- Power BI license scenarios -- Dataset design -- Data warehouse bus matrix -- Dataset design process -- Select the business process -- Declare the grain -- Identify the dimensions -- Define the facts -- Data profiling -- Data profiling with Power BI Desktop -- Dataset planning -- Data transformations -- Import, DirectQuery, Live, and Composite datasets -- Import mode -- DirectQuery/Live mode -- Composite mode -- Sample project analysis -- Summary -- Chapter 2: Preparing Data Sources -- Query folding -- Partial query folding -- Query design per dataset mode -- Import mode dataset queries -- DirectQuery dataset queries -- DirectQuery report execution -- Composite datasets -- Table storage modes -- 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 examples -- Date dimension view -- Mark as date table -- Product dimension view -- Slowly changing dimensions -- Summary -- Chapter 3: Connecting to Sources and Transforming Data with M -- Types of Power Query M queries -- Organizing queries -- Data source parameters -- Staging queries -- DirectQuery staging -- Fact and dimension queries Source reference only -- Excel workbook - Annual Sales Plan -- Parameter tables queries -- Security table queries -- Custom function queries -- Creating Power Query M queries -- Numeric data types -- Item access in M -- Power Query M query examples -- Trailing three years filter -- Combining queries -- Incremental refresh for fact tables -- Customer history column -- Product dimension integration -- R and Python script transformation -- Dataflows -- Power BI Premium dataflow features -- Power Query M editing tools -- Advanced Editor -- Visual Studio Code -- Visual Studio -- Summary -- Chapter 4: Designing Import, DirectQuery, and Composite Data Models -- Dataset layers -- Power BI as a superset of Azure Analysis Services -- Dataset objectives -- Competing objectives -- External factors -- The Data Model -- The Model 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 -- Parameter tables -- Measure groups -- Last refreshed date -- Measure support logic -- Display folders -- Relationships -- Uniqueness -- Ambiguity -- Single-direction relationships -- Direct flights only -- Bidirectional relationships -- Shared dimensions -- Date dimensions -- The CROSSFILTER function -- Model metadata -- Visibility -- Column and measure metadata -- Default summarization -- Data format -- Data category -- Description -- Optimizing data model performance -- Import -- Query caching -- Columnar compression -- Memory analysis via DMVs and the VertiPaq Analyzer -- DirectQuery -- Columnstore and HTAP -- Automatic aggregations -- Composite -- Aggregation tables -- Summary -- Chapter 5: Developing DAX Measures and Security Roles -- DAX measure basics -- Filter context -- SQL equivalent -- Measure evaluation process -- Row context Scalar and table functions -- Related tables -- The CALCULATE() function -- The FILTER() function -- DAX variables -- Base measures -- Measure support expressions -- KPI targets -- Current and prior periods -- Date intelligence metrics -- Current versus prior and growth rates -- Rolling periods -- Calculation groups -- Dimension metrics -- Missing dimensions -- Ranking metrics -- Dynamic ranking measures -- Security roles -- Dynamic row-level security -- Performance testing -- Performance analyzer -- DAX Studio -- Summary -- Chapter 6: Planning Power BI Reports -- Report planning process -- Identify the audience -- Define the business questions to answer -- Confirm that the dataset supports the business questions -- Determine interactivity -- Define access and distribution -- Sketch the report layout -- Report architecture diagram -- Visualization best practices -- Choosing the right visual -- Tables and matrices versus charts -- Chart selection -- Visualization anti-patterns -- Visual interactions -- Editing interactions -- Drillthrough report pages -- Custom labels and the back button -- Multi-column drillthrough -- Report filter scopes -- Report filter conditions -- Report and page filters -- Relative date filtering -- Visual-level filtering -- Top N visual-level filters -- Bookmarks -- Selection pane and the Spotlight property -- Custom report navigation -- View mode -- Live connections to Power BI datasets -- Customizing Live connection reports -- Switching Live source datasets -- Switching between import mode and Live mode datasets -- Report design summary -- Summary -- Chapter 7: Creating and Formatting Visualizations -- The Visualizations pane -- Slicers -- Slicer synchronization -- Custom slicer parameters -- What-if parameters -- Page filter or slicer? -- Single-value visuals -- The Card visual -- The KPI visual -- Gauge visual Map visuals -- Bubble map -- Filled map -- Waterfall chart -- Power Platform visuals -- Power Apps for Power BI -- Power Automate for Power BI -- Premium visuals -- Scorecard -- Paginated reports -- Elements -- Formatting visualizations -- Tooltips -- Report page tooltips -- Column and line charts -- Column and line chart conditional formatting -- Table and matrix visuals -- Custom format strings -- Table and matrix conditional formatting -- Sparklines -- Values as rows -- Scatter charts -- Summary -- Chapter 8: Applying Advanced Analytics -- AI visuals -- Key influencers -- Decomposition tree -- Q& -- A -- Smart narrative -- R and Python visuals -- R visual -- Python visual -- ArcGIS Maps for Power BI -- Custom visuals -- Adding a custom visual -- Animation and data storytelling -- Play axis for Scatter charts -- Pulse chart -- Analytics pane -- Trend line -- Forecasting -- Quick insights/Analyze -- Explain the increase/decrease -- Mobile-optimized report pages -- Summary -- Chapter 9: Designing Dashboards -- Dashboards versus reports -- Dashboard design -- Visual selection -- Layout -- Navigation pane -- Fullscreen mode -- Supporting tiles -- Dashboard architectures -- Single-dashboard architecture -- Multiple-dashboard architecture -- Organizational dashboard architecture -- Multiple datasets -- Dashboard tiles -- Tile details and custom links -- Real-time data tiles -- Dashboard themes -- Paginated reports -- Excel workbooks -- Live report pages -- Mobile-optimized dashboards -- Summary -- Chapter 10: Managing Workspaces and Content -- Workspaces -- Workspace roles and rights -- Viewer role -- Contributor role -- Member role -- Admin role -- Datasets across workspaces -- My workspace -- Staged deployments -- Workspace datasets -- Power BI REST API and PowerShell module -- Power BI REST API -- Power BI PowerShell module Workspace and content identifiers -- PowerShell sample scripts -- Power BI deployment pipelines -- Content sensitivity and protection -- Information protection -- Data loss prevention -- Version control -- OneDrive for Business -- Source control for M and DAX code -- MSHGQM -- Metadata management -- Field descriptions -- Creating descriptions -- View field descriptions -- Metadata Mechanic -- Metadata reporting -- Standard metadata reports -- Server and database parameters -- Querying the DMVs from Power BI -- Integrating and enhancing DMV data -- Metadata report pages -- Summary -- Chapter 11: Managing the On-Premises Data Gateway -- On-premises data gateway planning -- Top gateway planning tasks -- Determining whether a gateway is needed -- Identifying where the gateway should be installed -- Defining the gateway infrastructure and hardware requirements -- Defining gateway roles and permissions -- Planning for recovery keys -- Standard versus personal mode -- Gateway concepts -- Gateway clusters -- Gateway architectures -- Gateway security -- Gateway installation and configuration -- The gateway service account -- TCP versus HTTPS mode -- Connectors -- Recovery Keys -- Managing gateway clusters -- Gateway administrators -- Gateway data sources and users -- PowerShell support for gateway clusters -- Troubleshooting and monitoring gateways -- Restoring, migrating, and taking over a gateway -- Gateway diagnostics -- Gateway monitoring reports -- Data refresh -- Scheduled data refresh -- DirectQuery datasets -- Live connections to Analysis Services models -- Dashboard cache refresh -- Summary -- Chapter 12: Deploying Paginated Reports -- Paginated reports in the Power BI service -- Planning paginated reports -- Building and publishing paginated reports -- Identifying and interacting with paginated reports Printing, exporting, subscribing, and sharing |
| ctrlnum | (ZDB-30-PQE)EBC7016565 (ZDB-30-PAD)EBC7016565 (ZDB-89-EBL)EBL7016565 (OCoLC)1330935200 (DE-599)BVBBV048831058 |
| dewey-full | 658.05 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.05 |
| dewey-search | 658.05 |
| dewey-sort | 3658.05 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 2nd ed |
| format | Electronic eBook |
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| id | DE-604.BV048831058 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:35:28Z |
| indexdate | 2024-07-10T09:47:12Z |
| institution | BVB |
| isbn | 9781801818193 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034096635 |
| oclc_num | 1330935200 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (712 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Packt Publishing, Limited |
| record_format | marc |
| spelling | Deckler, Greg Verfasser aut Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence 2nd ed Birmingham Packt Publishing, Limited 2022 ©2022 1 Online-Ressource (712 Seiten) txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Cover -- CopyRight Page -- 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 administrator -- Project role collaboration -- Power BI licenses -- Shared capacity -- Free -- Pro -- Dedicated capacity -- Premium -- Premium Per User -- Embedded -- Power BI license scenarios -- Dataset design -- Data warehouse bus matrix -- Dataset design process -- Select the business process -- Declare the grain -- Identify the dimensions -- Define the facts -- Data profiling -- Data profiling with Power BI Desktop -- Dataset planning -- Data transformations -- Import, DirectQuery, Live, and Composite datasets -- Import mode -- DirectQuery/Live mode -- Composite mode -- Sample project analysis -- Summary -- Chapter 2: Preparing Data Sources -- Query folding -- Partial query folding -- Query design per dataset mode -- Import mode dataset queries -- DirectQuery dataset queries -- DirectQuery report execution -- Composite datasets -- Table storage modes -- 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 examples -- Date dimension view -- Mark as date table -- Product dimension view -- Slowly changing dimensions -- Summary -- Chapter 3: Connecting to Sources and Transforming Data with M -- Types of Power Query M queries -- Organizing queries -- Data source parameters -- Staging queries -- DirectQuery staging -- Fact and dimension queries Source reference only -- Excel workbook - Annual Sales Plan -- Parameter tables queries -- Security table queries -- Custom function queries -- Creating Power Query M queries -- Numeric data types -- Item access in M -- Power Query M query examples -- Trailing three years filter -- Combining queries -- Incremental refresh for fact tables -- Customer history column -- Product dimension integration -- R and Python script transformation -- Dataflows -- Power BI Premium dataflow features -- Power Query M editing tools -- Advanced Editor -- Visual Studio Code -- Visual Studio -- Summary -- Chapter 4: Designing Import, DirectQuery, and Composite Data Models -- Dataset layers -- Power BI as a superset of Azure Analysis Services -- Dataset objectives -- Competing objectives -- External factors -- The Data Model -- The Model 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 -- Parameter tables -- Measure groups -- Last refreshed date -- Measure support logic -- Display folders -- Relationships -- Uniqueness -- Ambiguity -- Single-direction relationships -- Direct flights only -- Bidirectional relationships -- Shared dimensions -- Date dimensions -- The CROSSFILTER function -- Model metadata -- Visibility -- Column and measure metadata -- Default summarization -- Data format -- Data category -- Description -- Optimizing data model performance -- Import -- Query caching -- Columnar compression -- Memory analysis via DMVs and the VertiPaq Analyzer -- DirectQuery -- Columnstore and HTAP -- Automatic aggregations -- Composite -- Aggregation tables -- Summary -- Chapter 5: Developing DAX Measures and Security Roles -- DAX measure basics -- Filter context -- SQL equivalent -- Measure evaluation process -- Row context Scalar and table functions -- Related tables -- The CALCULATE() function -- The FILTER() function -- DAX variables -- Base measures -- Measure support expressions -- KPI targets -- Current and prior periods -- Date intelligence metrics -- Current versus prior and growth rates -- Rolling periods -- Calculation groups -- Dimension metrics -- Missing dimensions -- Ranking metrics -- Dynamic ranking measures -- Security roles -- Dynamic row-level security -- Performance testing -- Performance analyzer -- DAX Studio -- Summary -- Chapter 6: Planning Power BI Reports -- Report planning process -- Identify the audience -- Define the business questions to answer -- Confirm that the dataset supports the business questions -- Determine interactivity -- Define access and distribution -- Sketch the report layout -- Report architecture diagram -- Visualization best practices -- Choosing the right visual -- Tables and matrices versus charts -- Chart selection -- Visualization anti-patterns -- Visual interactions -- Editing interactions -- Drillthrough report pages -- Custom labels and the back button -- Multi-column drillthrough -- Report filter scopes -- Report filter conditions -- Report and page filters -- Relative date filtering -- Visual-level filtering -- Top N visual-level filters -- Bookmarks -- Selection pane and the Spotlight property -- Custom report navigation -- View mode -- Live connections to Power BI datasets -- Customizing Live connection reports -- Switching Live source datasets -- Switching between import mode and Live mode datasets -- Report design summary -- Summary -- Chapter 7: Creating and Formatting Visualizations -- The Visualizations pane -- Slicers -- Slicer synchronization -- Custom slicer parameters -- What-if parameters -- Page filter or slicer? -- Single-value visuals -- The Card visual -- The KPI visual -- Gauge visual Map visuals -- Bubble map -- Filled map -- Waterfall chart -- Power Platform visuals -- Power Apps for Power BI -- Power Automate for Power BI -- Premium visuals -- Scorecard -- Paginated reports -- Elements -- Formatting visualizations -- Tooltips -- Report page tooltips -- Column and line charts -- Column and line chart conditional formatting -- Table and matrix visuals -- Custom format strings -- Table and matrix conditional formatting -- Sparklines -- Values as rows -- Scatter charts -- Summary -- Chapter 8: Applying Advanced Analytics -- AI visuals -- Key influencers -- Decomposition tree -- Q& -- A -- Smart narrative -- R and Python visuals -- R visual -- Python visual -- ArcGIS Maps for Power BI -- Custom visuals -- Adding a custom visual -- Animation and data storytelling -- Play axis for Scatter charts -- Pulse chart -- Analytics pane -- Trend line -- Forecasting -- Quick insights/Analyze -- Explain the increase/decrease -- Mobile-optimized report pages -- Summary -- Chapter 9: Designing Dashboards -- Dashboards versus reports -- Dashboard design -- Visual selection -- Layout -- Navigation pane -- Fullscreen mode -- Supporting tiles -- Dashboard architectures -- Single-dashboard architecture -- Multiple-dashboard architecture -- Organizational dashboard architecture -- Multiple datasets -- Dashboard tiles -- Tile details and custom links -- Real-time data tiles -- Dashboard themes -- Paginated reports -- Excel workbooks -- Live report pages -- Mobile-optimized dashboards -- Summary -- Chapter 10: Managing Workspaces and Content -- Workspaces -- Workspace roles and rights -- Viewer role -- Contributor role -- Member role -- Admin role -- Datasets across workspaces -- My workspace -- Staged deployments -- Workspace datasets -- Power BI REST API and PowerShell module -- Power BI REST API -- Power BI PowerShell module Workspace and content identifiers -- PowerShell sample scripts -- Power BI deployment pipelines -- Content sensitivity and protection -- Information protection -- Data loss prevention -- Version control -- OneDrive for Business -- Source control for M and DAX code -- MSHGQM -- Metadata management -- Field descriptions -- Creating descriptions -- View field descriptions -- Metadata Mechanic -- Metadata reporting -- Standard metadata reports -- Server and database parameters -- Querying the DMVs from Power BI -- Integrating and enhancing DMV data -- Metadata report pages -- Summary -- Chapter 11: Managing the On-Premises Data Gateway -- On-premises data gateway planning -- Top gateway planning tasks -- Determining whether a gateway is needed -- Identifying where the gateway should be installed -- Defining the gateway infrastructure and hardware requirements -- Defining gateway roles and permissions -- Planning for recovery keys -- Standard versus personal mode -- Gateway concepts -- Gateway clusters -- Gateway architectures -- Gateway security -- Gateway installation and configuration -- The gateway service account -- TCP versus HTTPS mode -- Connectors -- Recovery Keys -- Managing gateway clusters -- Gateway administrators -- Gateway data sources and users -- PowerShell support for gateway clusters -- Troubleshooting and monitoring gateways -- Restoring, migrating, and taking over a gateway -- Gateway diagnostics -- Gateway monitoring reports -- Data refresh -- Scheduled data refresh -- DirectQuery datasets -- Live connections to Analysis Services models -- Dashboard cache refresh -- Summary -- Chapter 12: Deploying Paginated Reports -- Paginated reports in the Power BI service -- Planning paginated reports -- Building and publishing paginated reports -- Identifying and interacting with paginated reports Printing, exporting, subscribing, and sharing Microsoft Power BI (Computer file) Business-Data processing Visual analytics Powell, Brett Sonstige oth Gordon, Leon Sonstige oth Erscheint auch als Druck-Ausgabe Deckler, Greg Mastering Microsoft Power BI Birmingham : Packt Publishing, Limited,c2022 |
| spellingShingle | Deckler, Greg Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence Cover -- CopyRight Page -- 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 administrator -- Project role collaboration -- Power BI licenses -- Shared capacity -- Free -- Pro -- Dedicated capacity -- Premium -- Premium Per User -- Embedded -- Power BI license scenarios -- Dataset design -- Data warehouse bus matrix -- Dataset design process -- Select the business process -- Declare the grain -- Identify the dimensions -- Define the facts -- Data profiling -- Data profiling with Power BI Desktop -- Dataset planning -- Data transformations -- Import, DirectQuery, Live, and Composite datasets -- Import mode -- DirectQuery/Live mode -- Composite mode -- Sample project analysis -- Summary -- Chapter 2: Preparing Data Sources -- Query folding -- Partial query folding -- Query design per dataset mode -- Import mode dataset queries -- DirectQuery dataset queries -- DirectQuery report execution -- Composite datasets -- Table storage modes -- 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 examples -- Date dimension view -- Mark as date table -- Product dimension view -- Slowly changing dimensions -- Summary -- Chapter 3: Connecting to Sources and Transforming Data with M -- Types of Power Query M queries -- Organizing queries -- Data source parameters -- Staging queries -- DirectQuery staging -- Fact and dimension queries Source reference only -- Excel workbook - Annual Sales Plan -- Parameter tables queries -- Security table queries -- Custom function queries -- Creating Power Query M queries -- Numeric data types -- Item access in M -- Power Query M query examples -- Trailing three years filter -- Combining queries -- Incremental refresh for fact tables -- Customer history column -- Product dimension integration -- R and Python script transformation -- Dataflows -- Power BI Premium dataflow features -- Power Query M editing tools -- Advanced Editor -- Visual Studio Code -- Visual Studio -- Summary -- Chapter 4: Designing Import, DirectQuery, and Composite Data Models -- Dataset layers -- Power BI as a superset of Azure Analysis Services -- Dataset objectives -- Competing objectives -- External factors -- The Data Model -- The Model 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 -- Parameter tables -- Measure groups -- Last refreshed date -- Measure support logic -- Display folders -- Relationships -- Uniqueness -- Ambiguity -- Single-direction relationships -- Direct flights only -- Bidirectional relationships -- Shared dimensions -- Date dimensions -- The CROSSFILTER function -- Model metadata -- Visibility -- Column and measure metadata -- Default summarization -- Data format -- Data category -- Description -- Optimizing data model performance -- Import -- Query caching -- Columnar compression -- Memory analysis via DMVs and the VertiPaq Analyzer -- DirectQuery -- Columnstore and HTAP -- Automatic aggregations -- Composite -- Aggregation tables -- Summary -- Chapter 5: Developing DAX Measures and Security Roles -- DAX measure basics -- Filter context -- SQL equivalent -- Measure evaluation process -- Row context Scalar and table functions -- Related tables -- The CALCULATE() function -- The FILTER() function -- DAX variables -- Base measures -- Measure support expressions -- KPI targets -- Current and prior periods -- Date intelligence metrics -- Current versus prior and growth rates -- Rolling periods -- Calculation groups -- Dimension metrics -- Missing dimensions -- Ranking metrics -- Dynamic ranking measures -- Security roles -- Dynamic row-level security -- Performance testing -- Performance analyzer -- DAX Studio -- Summary -- Chapter 6: Planning Power BI Reports -- Report planning process -- Identify the audience -- Define the business questions to answer -- Confirm that the dataset supports the business questions -- Determine interactivity -- Define access and distribution -- Sketch the report layout -- Report architecture diagram -- Visualization best practices -- Choosing the right visual -- Tables and matrices versus charts -- Chart selection -- Visualization anti-patterns -- Visual interactions -- Editing interactions -- Drillthrough report pages -- Custom labels and the back button -- Multi-column drillthrough -- Report filter scopes -- Report filter conditions -- Report and page filters -- Relative date filtering -- Visual-level filtering -- Top N visual-level filters -- Bookmarks -- Selection pane and the Spotlight property -- Custom report navigation -- View mode -- Live connections to Power BI datasets -- Customizing Live connection reports -- Switching Live source datasets -- Switching between import mode and Live mode datasets -- Report design summary -- Summary -- Chapter 7: Creating and Formatting Visualizations -- The Visualizations pane -- Slicers -- Slicer synchronization -- Custom slicer parameters -- What-if parameters -- Page filter or slicer? -- Single-value visuals -- The Card visual -- The KPI visual -- Gauge visual Map visuals -- Bubble map -- Filled map -- Waterfall chart -- Power Platform visuals -- Power Apps for Power BI -- Power Automate for Power BI -- Premium visuals -- Scorecard -- Paginated reports -- Elements -- Formatting visualizations -- Tooltips -- Report page tooltips -- Column and line charts -- Column and line chart conditional formatting -- Table and matrix visuals -- Custom format strings -- Table and matrix conditional formatting -- Sparklines -- Values as rows -- Scatter charts -- Summary -- Chapter 8: Applying Advanced Analytics -- AI visuals -- Key influencers -- Decomposition tree -- Q& -- A -- Smart narrative -- R and Python visuals -- R visual -- Python visual -- ArcGIS Maps for Power BI -- Custom visuals -- Adding a custom visual -- Animation and data storytelling -- Play axis for Scatter charts -- Pulse chart -- Analytics pane -- Trend line -- Forecasting -- Quick insights/Analyze -- Explain the increase/decrease -- Mobile-optimized report pages -- Summary -- Chapter 9: Designing Dashboards -- Dashboards versus reports -- Dashboard design -- Visual selection -- Layout -- Navigation pane -- Fullscreen mode -- Supporting tiles -- Dashboard architectures -- Single-dashboard architecture -- Multiple-dashboard architecture -- Organizational dashboard architecture -- Multiple datasets -- Dashboard tiles -- Tile details and custom links -- Real-time data tiles -- Dashboard themes -- Paginated reports -- Excel workbooks -- Live report pages -- Mobile-optimized dashboards -- Summary -- Chapter 10: Managing Workspaces and Content -- Workspaces -- Workspace roles and rights -- Viewer role -- Contributor role -- Member role -- Admin role -- Datasets across workspaces -- My workspace -- Staged deployments -- Workspace datasets -- Power BI REST API and PowerShell module -- Power BI REST API -- Power BI PowerShell module Workspace and content identifiers -- PowerShell sample scripts -- Power BI deployment pipelines -- Content sensitivity and protection -- Information protection -- Data loss prevention -- Version control -- OneDrive for Business -- Source control for M and DAX code -- MSHGQM -- Metadata management -- Field descriptions -- Creating descriptions -- View field descriptions -- Metadata Mechanic -- Metadata reporting -- Standard metadata reports -- Server and database parameters -- Querying the DMVs from Power BI -- Integrating and enhancing DMV data -- Metadata report pages -- Summary -- Chapter 11: Managing the On-Premises Data Gateway -- On-premises data gateway planning -- Top gateway planning tasks -- Determining whether a gateway is needed -- Identifying where the gateway should be installed -- Defining the gateway infrastructure and hardware requirements -- Defining gateway roles and permissions -- Planning for recovery keys -- Standard versus personal mode -- Gateway concepts -- Gateway clusters -- Gateway architectures -- Gateway security -- Gateway installation and configuration -- The gateway service account -- TCP versus HTTPS mode -- Connectors -- Recovery Keys -- Managing gateway clusters -- Gateway administrators -- Gateway data sources and users -- PowerShell support for gateway clusters -- Troubleshooting and monitoring gateways -- Restoring, migrating, and taking over a gateway -- Gateway diagnostics -- Gateway monitoring reports -- Data refresh -- Scheduled data refresh -- DirectQuery datasets -- Live connections to Analysis Services models -- Dashboard cache refresh -- Summary -- Chapter 12: Deploying Paginated Reports -- Paginated reports in the Power BI service -- Planning paginated reports -- Building and publishing paginated reports -- Identifying and interacting with paginated reports Printing, exporting, subscribing, and sharing Microsoft Power BI (Computer file) Business-Data processing Visual analytics |
| title | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_auth | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_exact_search | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_exact_search_txtP | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_full | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_fullStr | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_full_unstemmed | Mastering Microsoft Power BI Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| title_short | Mastering Microsoft Power BI |
| title_sort | mastering microsoft power bi expert techniques to create interactive insights for effective data analytics and business intelligence |
| title_sub | Expert Techniques to Create Interactive Insights for Effective Data Analytics and Business Intelligence |
| topic | Microsoft Power BI (Computer file) Business-Data processing Visual analytics |
| topic_facet | Microsoft Power BI (Computer file) Business-Data processing Visual analytics |
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