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Mastering Microsoft Power BI
Mastering Microsoft Power BI

Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence

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Mastering Microsoft Power BI

Planning Power BI Projects

In this chapter, we will walk through a Power BI project planning process from the perspective of an organization with an on-premises data warehouse and a supporting nightly extract-transform-load (ETL) process but no existing SSAS servers or IT-approved Power BI datasets. The business intelligence team will be responsible for the development of a Power BI dataset, including source queries, relationships, and metrics, in addition to a set of Power BI reports and dashboards.

Almost all business users will consume the reports and dashboards in the Power BI online service and via the Power BI mobile apps, but a few business analysts will also require the ability to author Power BI and Excel reports for their teams based on the new dataset. Power BI Pro licenses and Power BI Premium capacity will be used to support the development, scalability, and distribution requirements of the project.

In this chapter, we will review the following topics:

  • Power BI deployment modes
  • Project discovery and ingestion
  • Power BI project roles
  • Power BI licenses
  • Dataset design process
  • Dataset planning
  • Import and DirectQuery datasets

Power BI deployment modes

Organizations can choose to deliver and manage their Power BI deployment through IT and standard project workflows or to empower certain business users to take advantage of Self-Service BI capabilities with tools such as Power BI Desktop and Excel. In many scenarios, a combination of IT resources, such as the On-premises data gateway and Power BI Premium capacity, can be combined with the business users' knowledge of requirements and familiarity with data analysis and visualization.

Organizations may also utilize alternative deployment modes per project or with different business teams based on available resources and the needs of the project. The greatest value from Power BI deployments can be obtained when the technical expertise and governance of Corporate BI solutions are combined with the data exploration and analysis features, which can be made available to all users. The scalability and accessibility of Power BI solutions to support thousands of users, including read-only users who have not been assigned Power BI Pro licenses, is made possible by provisioning Power BI Premium capacity, as described in the final three chapters of this book.

Corporate BI

The Corporate BI delivery approach in which the BI team develops and maintains both the Power BI dataset (data model) and the required report visualizations is a common deployment option, particularly for large-scale projects and projects with executive-level sponsors or stakeholders. This is the approach followed in this chapter and throughout this book, as it offers maximum control over top BI objectives, such as version control, scalability, usability, and performance.

However, as per the following Power BI deployment modes diagram, there are other approaches in which business teams own or contribute to the solution:

Power BI deployment modes

A Power BI dataset is a semantic data model composed of data source queries, relationships between dimensions and fact tables, and measurement calculations. The Power BI Desktop application can be used to create datasets as well as merely connect to existing datasets to author Power BI reports. The Power BI Desktop shares the same data retrieval and modeling engines as the latest version of SQL Server Analysis Services (SSAS) in tabular mode and Azure Analysis Services, Microsoft's enterprise BI modeling solution. Many BI/IT organizations utilize Analysis Services models as the primary data source for Power BI projects and it's possible to migrate Power BI Desktop files (.pbix) to Analysis Services models, as described in Chapter 13, Scaling with Premium and Analysis Services.

Self-service approaches can benefit both IT and business teams, as they can reduce IT resources, project timelines, and provide the business with a greater level of flexibility as their analytical needs change. Additionally, Power BI projects can be migrated across deployment modes over time as required skills and resources change. However, greater levels of self-service and shared ownership structures can also increase the risk of miscommunication and introduce issues of version control, quality, and consistency.

Self-Service Visualization

In the Self-Service Visualization approach, the dataset is created and maintained by the IT organization's BI team, but certain business users with Power BI Pro licenses create reports and dashboards for consumption by other users. In many scenarios, business analysts are already comfortable with authoring reports in Power BI Desktop (or, optionally, Excel) and can leverage their business knowledge to rapidly develop useful visualizations and insights. Given ownership of the dataset, the BI team can be confident that only curated data sources and standard metric definitions are used in reports and can ensure that the dataset remains available, performant, and updated, or refreshed as per business requirements.

Self-Service BI

In the Self-Service BI approach, the BI organization only contributes essential infrastructure and monitoring, such as the use of an On-premises data gateway and possibly Power Premium capacity to support the solution. Since the business team maintains control of both the dataset and the visualization layer, the business team has maximum flexibility to tailor its own solutions including data source retrieval, transformation, and modeling. This flexibility, however, can be negated by a lack of technical skills (for example, DAX measures) and a lack of technical knowledge such as the relationships between tables in a database. Additionally, business-controlled datasets can introduce version conflicts with corporate semantic models and generally lack the resilience, performance, and scalability of IT-owned datasets.

It's usually necessary or at least beneficial for BI organizations to own the Power BI datasets or at least the datasets which support important, widely distributed reports and dashboards. This is primarily due to the required knowledge of dimensional modeling best practices and the necessary technical skills in the M and DAX functional languages to develop sustainable datasets. Additionally, BI organizations require control of datasets to implement row-level security (RLS) and to maintain version control. Therefore, small datasets initially created by business teams are often migrated to the BI team and either integrated into larger models or rationalized given the equivalent functionality from an existing dataset.

Choosing a deployment mode

Larger organizations with experience of deploying and managing Power BI often utilize a mix of deployment modes depending on the needs of the project and available resources. For example, a Corporate BI solution with a set of standard IT developed reports and dashboards distributed via a Power BI app may be extended by assigning Power BI Pro licenses to certain business users who have experience or training in Power BI report design. These users could then leverage the existing data model and business definitions maintained by IT to create new reports and dashboards and distribute this content in a separate Power BI app to distinguish ownership.

An app workspace is simply a container of datasets, reports, and dashboards in the Power BI cloud service that can be distributed to large groups of users. A Power BI app represents the published version of an app workspace in the Power BI service and workspace. Members can choose which items in the workspace are included in the published Power BI app. See Chapter 8, Managing Application Workspaces and Power BI Content, and Chapter 11, Creating Power BI Apps and Content Distribution, for greater detail on app workspaces and apps, respectively.

Another common scenario is a proof-of-concept (POC) or small-scale self-service solution developed by a business user or a team to be transitioned to a formal, IT-owned, and managed solution. Power BI Desktop's rich graphical interfaces at each layer of the application (query editor, data model, and report canvas) make it possible and often easy for users to create useful models and reports with minimal experience and little to no code. It's much more difficult, of course, to deliver consistent insights across business functions (that is, finance, sales, and marketing) and at scale in a secure, governed environment. The IT organization can enhance the quality and analytical value of these assets as well as provide robust governance and administrative controls to ensure that the right data is being accessed by the right people.

The following list of fundamental questions will help guide a deployment mode decision:

  1. Who will own the data model?
    • Experienced dataset designers and other IT professionals are usually required to support complex data transformations, analytical data modeling, large data sizes, and security rules, such as RLS roles, as described in Chapter 4, Developing DAX Measures and Security Roles
    • If the required data model is relatively small and simple, or if the requirements are unclear, the business team may be best positioned to create at least the initial iterations of the model
    • The data model could be created with Analysis Services or Power BI Desktop
  2. Who will own the reports and dashboards?
    • Experienced Power BI report developers with an understanding of corporate standards and data visualization best practices can deliver a consistent user experience
    • Business users can be trained on report design and development practices and are well-positioned to manage the visualization layer, given their knowledge of business needs and questions
  3. How will the Power BI content be managed and distributed?
    • A staged deployment across development, test, and production environments, as described in Chapter 8, Managing Application Workspaces and Content, helps to ensure that quality, validated content is published. This approach is generally exclusive to Corporate BI projects.
    • Sufficient Power BI Premium capacity is required to support distribution to Power BI Free users and either large datasets or demanding query workloads.
    • Self-Service BI content can be assigned to Premium Capacity, but organizations may wish to limit the scale or scope of these projects to ensure that provisioned capacity is being used efficiently.

Project discovery and ingestion

A set of standard questions within a project template form can be used to initiate Power BI projects. Business guidance on these questions informs the BI team of the high-level technical needs of the project and helps to promote a productive project kickoff.

By reviewing the project template, the BI team can ask the project sponsor or relevant subject matter experts (SMEs) targeted questions to better understand the current state and the goals of the project.

Sample Power BI project template

The primary focus of the project-planning template and the overall project planning stage is on the data sources and the scale and structure of the Power BI dataset required. The project sponsor or business users may only have an idea of several reports, dashboards, or metrics needed but, as a Corporate BI project, it's essential to focus on where the project fits within an overall BI architecture and the long-term return on investment (ROI) of the solution. For example, BI teams would look to leverage any existing Power BI datasets or SSAS tabular models applicable to the project and would be sensitive to version-control issues.

Sample template – Adventure Works BI

The template is comprised of two tables. The first table answers the essential who and when questions so that the project can be added to the BI team's backlog. The BI team can use this information to plan their engagements across multiple ongoing and requested Power BI projects and to respond to project stakeholders, such as Vickie Jacobs, VP of Group Sales, in this example:

Date of Submission

10/15/2017

Project Sponsor

Vickie Jacobs, VP of Group Sales

Primary Stakeholders

Adventure Works Sales
Adventure Works Corp

Power BI Author(s)

Mark Langford, Sales Analytics Manager

The following table is a list of questions that describe the project's requirements and scope. For example, the number of users that will be read-only consumers of Power BI reports and dashboards, and the number of self-service users that will need Power BI Pro licenses to create Power BI content will largely impact the total cost of the project.

Likewise, the amount of historical data to include in the dataset (2 years, 5 years?) can significantly impact performance scalability:

Topic

#

Question

Business Input

Data sources

1

Can you describe the required data? (For example, sales, inventory, shipping).

Internet Sales, Reseller Sales, and the Sales and Margin Plan. We need to analyze total corporate sales, online, and reseller sales, and compare these results to our plan.

Data sources

2

Is all of the data required for your project available in the data warehouse (SQL Server)?

No

Data Sources

3

What other data sources (if any) contain all or part of the required data (for example, Web, Oracle, Excel)?

The Sales and Margin Plan is maintained in Excel.

Security

4

Should certain users be prevented from viewing some or all of the data?

Yes, sales managers and associates should only see data for their sales territory group. VPs of sales, however, should have global access.

Security

5

Does the data contain any PCII or sensitive data?

No, not that I’m aware of

Scale

6

Approximately, how many years of historical data are needed?

3-4

Data refresh

7

How often does the data need to be refreshed?

Daily

Data refresh

8

Is there a need to view data in real time (as it changes)?

No

Distribution

9

Approximately, how many users will need to view reports and dashboards?

200

Distribution

10

Approximately, how many users will need to create reports and dashboards?

3-4

Version control

11

Are there existing reports on the same data? If so, please describe.

Yes, there are daily and weekly sales snapshot reports available on the portal. Additionally, our team builds reports in Excel that compare actuals to plan.

Version Control

12

Is the Power BI solution expected to replace these existing reports?

Yes, we would like to exclusively use Power BI going forward.

A business analyst inside the IT organization can partner with the business on completing the project ingestion template and review the current state to give greater context to the template. Prior to the project kickoff meeting, the business analyst can meet with the BI team members to review the template and any additional findings or considerations.

Many questions with greater levels of detail will be raised as the project moves forward and therefore the template shouldn't attempt to be comprehensive or overwhelm business teams. The specific questions to include should use business-friendly language and serve to call out the top drivers of project resources and Corporate BI priorities, such as security and version control.
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Key benefits

  • 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

Description

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 Power BI.

Who is this book 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

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Table of Contents

14 Chapters
Planning Power BI Projects Chevron down icon Chevron up icon
Connecting to Sources and Transforming Data with M Chevron down icon Chevron up icon
Designing Import and DirectQuery Data Models Chevron down icon Chevron up icon
Developing DAX Measures and Security Roles Chevron down icon Chevron up icon
Creating and Formatting Power BI Reports Chevron down icon Chevron up icon
Applying Custom Visuals, Animation, and Analytics Chevron down icon Chevron up icon
Designing Power BI Dashboards and Architectures Chevron down icon Chevron up icon
Managing Application Workspaces and Content Chevron down icon Chevron up icon
Managing the On-Premises Data Gateway Chevron down icon Chevron up icon
Deploying the Power BI Report Server Chevron down icon Chevron up icon
Creating Power BI Apps and Content Distribution Chevron down icon Chevron up icon
Administering Power BI for an Organization Chevron down icon Chevron up icon
Scaling with Premium and Analysis Services Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

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Georgia Jaunt Sep 18, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is one of the most information-dense technical reference books I've read in a long time. By this I mean -- it packs a tremendous amount of useful detail on each page. I'm coming from this as a 20+ year user of database tools, MCSA in SQL Server and someone motivated to really learn/apply Power BI as a consultant. This book really delivers in terms of in-depth explanations and content you can use to create PBI solutions. It goes above and beyond in another dimension as well: the authors very useful digressions on best-practises and real-world advice for things like visualizations and frameworks for managing users' competing needs. This is truly a useful text for someone interested in designing / deploying / managing mid-size corporate installations of BI solutions using Microsoft tools.Caution -- This is not an introductory text. If you are interested in casual use of PBI, there are probably more accessible books out there.It is easy to give this 5 stars on its content -- but would also mention a couple of minor things: - the included code samples are not directly useable. The author cautions about this in the text. Of 3 points raised, this is this the most significant. It would have been nice to be able to eyeball the worked examples on my workstation. - Minor: The index in the back is pretty sparse. For example, you won't find "hierarchy" mentioned anywhere there but have to read through the table of contents to find that section. - Minor: The printing / paper / binding quality is fine -- but I wish Packt would put more thought into typography. It's easier to digest this kind of material when the publisher uses more finesse in use of different sized/numbered heads. As-is, the chapter content just seems to run together.FWIW -- I've previously read: - Teo Lachev's "Applied MS PowerBI" (2nd ed) -- which is also good, particularly for someone first experimenting with Power BI. - Russo & Ferrari "Definitive Guide to Dax" (1st ed) -- the go-to reference on DAX.Aside: I have no affiliation with the author or publisher. I purchased this on Amazon, etc.
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maridee oday May 12, 2018
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I just started this book and already have found it incredibly useful. I relied heavily on Brett's first book in my Power BI work. This new one is wonderful and updated to include the latest features. What I love about Brett's books is that he provides a higher level view than the Microsoft free online education, so you can understand how the different features and methods of doing things interact and compare before diving into the details, which are also provided in a clear and concise way. The information is presented from the ground-up in a logical manner that promotes a solid foundation for learning. In addition, I can easily skim the Table of Contents to find exactly what I need, and it covers every essential Power BI topic. Brett is truly the premier author for books in this field.
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JPH Apr 30, 2019
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Très complet, clair et riche : Une mine de renseignements...
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Brian Hanson Oct 03, 2018
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If you're looking for enterprise-level Power BI deployment, this is the bible. I learned a lot about best practices, and what I already knew was explained very clearly.
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Richard Walker Jan 30, 2019
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I have found this to be a thorough and extremely useful tool to plan the development and scaling of internal and external solutions for PowerBI and Azure AD B2B. This is a great add on to other books written by the likes of Ferrari and Russo.
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