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Mastering Microsoft Power BI电子书

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28人正在读 | 0人评论 6.2

作       者:Brett Powell

出  版  社:Packt Publishing

出版时间:2018-03-29

字       数:82.1万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Design, create and manage robust Power BI solutions to gain meaningful business insights About This Book ? Master all the dashboarding and reporting features of Microsoft Power BI ? Combine data from multiple sources, create stunning visualizations and publish your reports across multiple platforms ? A comprehensive guide with real-world use cases and examples demonstrating how you can get the best out of Microsoft Power BI Who This Book Is For Business Intelligence professionals and existing Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book to be useful. While understanding of the basic BI concepts is required, some exposure to Microsoft Power BI will be helpful. What You Will Learn ? Build efficient data retrieval and transformation processes with the Power Query M Language ? Design scalable, user-friendly DirectQuery and Import Data Models ? Develop visually rich, immersive, and interactive reports and dashboards ? Maintain version control and stage deployments across development, test, and production environments ? Manage and monitor the Power BI Service and the On-premises data gateway ? Develop a fully on-premise solution with the Power BI Report Server ? Scale up a Power BI solution via Power BI Premium capacity and migration to Azure Analysis Services or SQL Server Analysis Services In Detail This book is intended for business intelligence professionals responsible for the design and development of Power BI content as well as managers, architects and administrators who oversee Power BI projects and deployments. The chapters flow from the planning of a Power BI project through the development and distribution of content to the administration of Power BI for an organization. BI developers will learn how to create sustainable and impactful Power BI datasets, reports, and dashboards. This includes connecting to data sources, shaping and enhancing source data, and developing an analytical data model. Additionally, top report and dashboard design practices are described using features such as Bookmarks and the Power KPI visual. BI managers will learn how Power BI’s tools work together such as with the On-premises data gateway and how content can be staged and securely distributed via Apps. Additionally, both the Power BI Report Server and Power BI Premium are reviewed. By the end of this book, you will be confident in creating effective charts, tables, reports or dashboards for any kind of data using the tools and techniques in Microsoft PowerBI. Style and approach This book consists of real-world examples on Power BI that target novices as well as intermediate Power BI users. It goes deep into the technical issues, covers additional protocols, and many more real-live examples.
目录展开

Title Page

Copyright and Credits

Mastering Microsoft Power BI

Dedication

Packt Upsell

Why subscribe?

PacktPub.com

Contributors

About the author

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

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 process

Declaring 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

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 examples

Date 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 tools

Advanced Editor

Visual Studio Code

Visual Studio

Summary

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 relationships

Shared 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

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

Base measures

Measure support expressions

KPI Targets

Current and prior periods

Date intelligence metrics

Current versus prior and growth rates

Rolling periods

Dimension metrics

Missing dimensions

Ranking metrics

Dynamic ranking measures

Security roles

Dynamic row-level security

Performance testing

DAX Studio

Tracing a Power BI dataset via DAX Studio

Summary

Creating and Formatting Power BI Reports

Report planning

Power BI report architecture

Live connections to Power BI datasets

Customizing Live connection reports

Switching source datasets

Visualization best practices

Visualization anti-patterns

Choosing the visual

Tables versus charts

Chart selection

Visual interactions

Edit interactions

What-if parameters

Slicers

Slicer synchronization

Custom slicer parameters

Report filter scopes

Report filter conditions

Report and page filters

Page filter or slicer?

Relative date filtering

Visual-level filtering

Top N visual-level filters

Visualization formatting

Visual-level formatting

Line and column charts

Tooltips

Report page tooltips

Column and line chart conditional formatting

Column chart conditional formatting

Line chart conditional formatting

Table and matrix

Table and matrix conditional formatting

Values as rows

Scatter charts

Map visuals

Bubble map

Filled map

Mobile-optimized reports

Responsive visuals

Report design summary

Summary

Applying Custom Visuals, Animation, and Analytics

Drillthrough report pages

Custom labels and the back button

Multi-column drillthrough

Bookmarks

Selection pane and the Spotlight property

Custom report navigation

View mode

ArcGIS Map visual for Power BI

ArcGIS Maps Plus subscriptions

Waterfall chart breakdown

Analytics pane

Trend Line

Forecast line

Quick Insights

Explain the increase/decrease

Custom visuals

Adding a custom visual

Power KPI visual

Chiclet Slicer

Impact Bubble Chart

Dot Plot by Maq Software

Animation and data storytelling

Play axis for scatter charts

Pulse Chart

Summary

Designing Power BI Dashboards and Architectures

Dashboards versus reports

Dashboard design

Visual selection

Layout

Navigation pane

Full screen mode

Supporting tiles

Custom date filters

Multi-dashboard architectures

Single-dashboard architecture

Multiple-dashboard architecture

Organizational dashboard architecture

Multiple datasets

Dashboard tiles

Tile details and custom links

Images and text boxes

SQL Server Reporting Services

Excel workbooks

Live report pages

Mobile-optimized dashboards

Summary

Managing Application Workspaces and Content

Application workspaces

Workspace roles and rights

Workspace admins

Workspace members

My Workspace

Staged deployments

Workspace datasets

Power BI REST API

Client application ID

Workspace and content IDs

PowerShell sample scripts

Dashboard data classifications

Version control

OneDrive for Business version history

Source control for M and DAX code

Metadata management

Field descriptions

Creating descriptions

View field descriptions

Metadata reporting

Query field descriptions

Standard metadata reports

Server and database parameters

Querying the DMVs from Power BI

Integrating and enhancing DMV data

Metadata report pages

Summary

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

On-premises data gateway versus personal mode

Gateway clusters

Gateway architectures

Gateway security

Gateway configuration

The gateway service account

TCP versus HTTPS mode

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 log files

Performance Monitor counters

Scheduled data refresh

DirectQuery datasets

Single sign-on to DirectQuery sources via Kerberos

Live connections to Analysis Services models

Azure Analysis Services refresh

Dashboard cache refresh

Summary

Deploying the Power BI Report Server

Planning for the Power BI Report Server

Feature differences with the Power BI service

Parity with SQL Server Reporting Services

Data sources and connectivity options

Hardware and user licensing

Pro licenses for report authors

Alternative and hybrid deployment models

Report Server reference topology

Installation

Hardware and software requirements

Analysis Services Integrated

Retrieve the Report Server product key

Migrating from SQL Server Reporting Services

Configuration

Service Account

Remote Report Server Database

Office Online Server for Excel Workbooks

Upgrade cycles

Report Server Desktop Application

Running desktop versions side by side

Report Server Web Portal

Scheduled data refresh

Data source authentication

Power BI mobile applications

Report server administration

Securing Power BI report content

Execution logs

Scale Power BI Report Server

Summary

Creating Power BI Apps and Content Distribution

Content distribution methods

Power BI apps

Licensing apps

App deployment process

User permissions

Publishing apps

Installing apps

Apps on Power BI mobile

App updates

Dataset-to-workspace relationship

Self-Service BI workspace

Self-Service content distribution

Risks to Self-Service BI

Sharing dashboards and reports

Sharing scopes

Sharing versus Power BI apps

SharePoint Online embedding

Custom application embedding

Publish to web

Data alerts

Microsoft Flow integration

Email Subscriptions

Analyze in Excel

Power BI Publisher for Excel

Summary

Administering Power BI for an Organization

Data governance for Power BI

Implementing data governance

Azure Active Directory

Azure AD B2B collaboration

Licensing external users

Conditional access policies

Power BI Admin Portal

Usage metrics

Users and Audit logs

Tenant settings

Embed Codes

Organizational Custom visuals

Usage metrics reports

Audit logs

Audit log monitoring solutions

Audit logs solution template

Power BI Premium capacities

Capacity allocation

Create, size, and monitor capacities

Change capacity size

Monitor premium capacities

App workspace assignment

Capacity admins

Summary

Scaling with Premium and Analysis Services

Power BI Premium

Power BI Premium capabilities

Corporate Power BI datasets

Limitation of Corporate BI datasets – Reusability

Premium capacity nodes

Frontend versus backend resources

Power BI Premium capacity allocation

Corporate and Self-Service BI capacity

Power BI Premium resource utilization

Data model optimizations

Report and visualization optimizations

Premium capacity estimations

Analysis Services

Analysis Services Models versus Power BI Desktop

Scale

Usability

Development and management tools

Azure Analysis Services versus SSAS

SSAS to Azure AS Migration

Provision Azure Analysis Services

Migration of Power BI Desktop to Analysis Services

Summary

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