CI/CD pipeline for Power BI deployments

 A CI/CD pipeline for Power BI deployments is an automated process that streamlines the development, testing, and deployment of Power BI reports and dashboards across different environments (like development, testing, and production) by using tools like Azure DevOps to manage the workflow, ensuring consistent quality and minimizing manual intervention throughout the deployment process. 

Key components of a Power BI CI/CD pipeline:

• Source Control:

  Storing Power BI PBIX files in a version control system like Git to track changes and manage different versions. 
• Build Stage:
• • Validation Checks: Performing quality checks on Power BI files, such as data connectivity, data quality, and report layout. 
  • Packaging: Creating a deployment package containing the Power BI content ready for deployment. 
• Test Stage:

• Unit Testing: Running automated tests on individual components of the Power BI report (e.g., visuals, calculations) to identify issues early. 
• User Acceptance Testing (UAT): Providing a controlled environment for end-users to test the functionality and usability of the Power BI content. 

Deployment Stage:

• Environment Management: Deploying the Power BI content to different environments (development, staging, production) based on the pipeline stage.
• Permissions Management: Assigning appropriate user access levels to Power BI workspaces and content based on the environment. 

Benefits of using a CI/CD pipeline for Power BI deployments:

• Faster Time to Market:

  Streamlines the deployment process, allowing quicker delivery of Power BI reports and updates to users.

Improved Quality:

• Automated testing catches errors early in the development cycle, leading to higher quality deployments.

Reduced Manual Effort:

• Automates repetitive tasks, freeing up developers to focus on more complex aspects of Power BI development.

Traceability:

• Provides a clear audit trail of changes made to Power BI content and who made them. 

Tools to implement a Power BI CI/CD pipeline:

• Azure DevOps:

  A comprehensive platform with built-in features for CI/CD pipelines, including the ability to manage Power BI deployments.

Power BI REST API:

• Can be used to programmatically interact with Power BI service to automate deployment tasks. 

Power BI Embedded:

• For integrating Power BI content into custom applications, enabling more granular control over deployment. 

Visualization Types in Power BI

Visualization Types in Power BI

Below are just some of the many different types of visualizations that can be added to Power BI reports, specified in Q&A, and pinned to dashboards.

Area charts: Basic (Layered) and Stacked

The Basic Area chart is based on the line chart with the area between the axis and line filled in.

Bar and column charts

Bar charts are the standard for looking at a specific value across different categories.

Cards: Multi row

Cards: Single number

Donut charts

Donut charts are similar to pie charts. They show the relationship of parts to a whole.

Gauge charts

Displays current status in the context of a goal.

KPIs

Displays progress toward a measurable goal.

Line charts

Emphasize the overall shape of an entire series of values, usually over time.

Maps: Basic maps

Used to associate both categorical and quantitative information with spatial locations.

Matrix

A table supports two dimensions, but a matrix makes it easier to display data meaningfully across multiple dimensions -- it supports a stepped layout. The matrix automatically aggregates the data and enables drill down.

Pie charts

Pie charts show the relationship of parts to a whole.

Q&A visual

The Q&A visual lets you ask questions about your data using natural language.

Tables

Work well with quantitative comparisons among items where there are many categories.

Treemaps

Are charts of colored rectangles, with size representing value. They can be hierarchical, with rectangles nested within the main rectangles.

Waterfall charts

Waterfall charts show a running total as values are added or subtracted.

These are some of the out-of-the-box Power BI visuals available from the visualization pane in Power BI Desktop and Power BI Service. However, sometimes you need a more custom visual and these can be found in AppSource for Power BI.

Administrator roles related to Power BI

 Administrator roles related to Power BI

There are several roles that work together to administer Power BI for your organization. Most admin roles are assigned in the Microsoft 365 admin center or by using PowerShell. The Power BI Premium Capacity and Power BI Embedded Capacity admin roles are assigned when the capacity is created. To learn more about each of the admin roles, 

ADMINISTRATOR ROLES RELATED TO POWER BI

Type of administrator	Administrative scope	Power BI tasks
Global admin	Microsoft 365	Has unlimited access to all management features for the organization
		Assigns roles to other users
Billing admin	Microsoft 365	Manage subscriptions
		Purchase licenses
License admin	Microsoft 365	Assign or remove licenses for users
User admin	Microsoft 365	Create and manage users and groups
		Reset user passwords
Power BI admin	Power BI service	Full access to Power BI management tasks
		Enable and disable Power BI features
		Report on usage and performance
		Review and manage auditing
Power BI Premium Capacity admin	A single Premium capacity	Assign workspaces to the capacity
		Manage user permission to the capacity
		Manage workloads to configure memory usage
		Restart the capacity
Power BI Embedded Capacity admin	A single Embedded capacity	Assign workspaces to the capacity
		Manage user permission to the capacity
		Manage workloads to configure memory usage
		Restart the capacity

Types of Filters in Power BI 

The four types of filters are:

• Report – Applies to all pages in the report.

• Page – Applies to all the visuals on the current report page.

• Visual – Applies to a single visual on a report page. You only see visual level filters if you have selected a visual on the report canvas.

• Drillthrough – Allows you to explore successively more detailed views within a single visual.

Parts of Power BI Desktop environment

 Parts of Power BI Desktop environment

In Power BI Desktop, you'll begin to build reports in the Report view. You'll be working in five main areas:

1. Ribbon - Displays common tasks that are associated with reports and visualizations.
2. Report view, or canvas - Where visualizations are created and arranged. You can switch between Report, Data, and Model views by selecting the icons in the left column.
3. Pages tab - Located along the bottom of the page, this area is where you would select or add a report page.
4. Visualizations pane - Where you can change visualizations, customize colors or axes, apply filters, drag fields, and more.
5. Fields pane - Where query elements and filters can be dragged onto the Report view or dragged to the Filters area of the Visualizations pane.

 

Basic building blocks in Power BI

1. Visualizations – A visual representation of data, sometimes just called visuals
2. Datasets – A collection of data that Power BI uses to create visualizations
3. Reports – A collection of visuals from a dataset, spanning one or more pages
4. Dashboards – A single-page collection of visuals built from a report
5. Tiles – A single visualization on a report or dashboard

Power BI Level measures ALLEXCEPT

 Power BI Level measures 

ALLEXCEPT

Removes all context filters in the table except filters that have been applied to the specified columns.

Syntax

DAX

ALLEXCEPT(<table>,<column>[,<column>[,…]])  

Parameters

PARAMETERS

Term	Definition
table	The table over which all context filters are removed, except filters on those columns that are specified in subsequent arguments.
column	The column for which context filters must be preserved.

The first argument to the ALLEXCEPT function must be a reference to a base table; all subsequent arguments must be references to base columns. You cannot use table expressions or column expressions with the ALLEXCEPT function.

Return value

A table with all filters removed except for the filters on the specified columns.

Remarks

• This function is not used by itself, but serves as an intermediate function that can be used to change the set of results over which some other calculation is performed.

• As described in the following table, you can use the ALL and ALLEXCEPT functions in different scenarios.

  TABLE 2

  Function and usage	Description
  ALL(Table)	Removes all filters from the specified table. In effect, ALL(Table) returns all of the values in the table, removing any filters from the context that otherwise might have been applied. This function is useful when you are working with many levels of grouping, and want to create a calculation that creates a ratio of an aggregated value to the total value.
  ALL (Column[, Column[, …]])	Removes all filters from the specified columns in the table; all other filters on other columns in the table still apply. All column arguments must come from the same table. The ALL(Column) variant is useful when you want to remove the context filters for one or more specific columns and to keep all other context filters.
  ALLEXCEPT(Table, Column1 [,Column2]...)	Removes all context filters in the table except filters that are applied to the specified columns. This is a convenient shortcut for situations in which you want to remove the filters on many, but not all, columns in a table.

• This function is not supported for use in DirectQuery mode when used in calculated columns or row-level security (RLS) rules.

Example

The following example presents a formula that you can use in a measure.

The formula sums SalesAmount_USD and uses the ALLEXCEPT function to remove any context filters on the DateTime table except if the filter has been applied to the CalendarYear column.

DAX

= CALCULATE(SUM(ResellerSales_USD[SalesAmount_USD]), ALLEXCEPT(DateTime, DateTime[CalendarYear]))  

Because the formula uses ALLEXCEPT, whenever any column but CalendarYear from the table DateTime is used to slice the PivotTable, the formula will remove any slicer filters, providing a value equal to the sum of SalesAmount_USD for the column label value, as shown in Table 1.

However, if the column CalendarYear is used to slice the PivotTable, the results are different. Because CalendarYear is specified as the argument to ALLEXCEPT, when the data is sliced on the year, a filter will be applied on years at the row level, as shown in Table 2. The user is encouraged to compare these tables to understand the behavior of ALLEXCEPT().

This article is used from MSFT documents.

Power BI Notes

Free workspace  dataset refresh max of 8 times a day
Premium workspace dataset refresh 48 times a day

Power BI user roles: Admin, Member, Contributor

Switch Statement Power BI

Column =
SWITCH (
    TRUE (),
    'Table'[Field1] = "AAA", "RETAIL",
    'Table'[Field1] = "BBB", "ONLINE",
    SEARCH ( "CCC", 'Table'[Field2], 1, 0 ) = 1, and 'Table'[Field1] like '%yyy%', "RETAIL",
    'Table'[Field2] = "DDD", "RETAIL",
    "UNKNOWN"
)

Power BI Premium Calculator

AT times it will be confusing what kind of capacity like P1, P2 or P3 need to be purchased for the organization implementing Power BI, Microsoft link below makes it easy to calculate the costs just by entering the number of users:

https://powerbi.microsoft.com/en-us/calculator/

Power BI DAX

What is DAX?

DAX is a collection of functions, operators, and constants that can be used in a formula, or expression, to calculate and return one or more values. Stated more simply, DAX helps you create new information from data already in your model.

Syntax

Before you create your own formulas, let’s take a look at DAX formula syntax. Syntax includes the various elements that make up a formula, or more simply, how the formula is written. For example, here's a simple DAX formula for a measure:

This formula includes the following syntax elements:

A. The measure name, Total Sales.

B. The equals sign operator (=), which indicates the beginning of the formula. When calculated, it will return a result.

C. The DAX function SUM, which adds up all of the numbers in the Sales[SalesAmount] column. You’ll learn more about functions later.

D. Parenthesis (), which surround an expression that contains one or more arguments. All functions require at least one argument. An argument passes a value to a function.

E. The referenced table, Sales.

F. The referenced column, [SalesAmount], in the Sales table. With this argument, the SUM function knows on which column to aggregate a SUM.

This name is known as a fully qualified column name in that it includes the column name preceded by the table name.  Columns referenced in the same table don't require the table name be included in the formula, which can make long formulas that reference many columns shorter and easier to read. However, it's a good practice to include the table name in your measure formulas, even when in the same table.

When trying to understand a DAX formula, it's often helpful to break down each of the elements into a language you think and speak every day. For example, you can read this formula as:

For the measure named Total Sales, calculate (=) the SUM of values in the [SalesAmount ] column in the Sales table.