DA-100 Exam Study Guide (Analyzing Data with Microsoft Power BI)

DA-100 Certificate EXAM STUDY GUIDE (ANALYZING DATA WITH MICROSOFT POWER BI)

Preparing for the DA-100 Analyzing Data with Microsoft Power BI Certificate exam? Don’t know where to start? This post is the DA-100 Certificate Study Guide (with links to each exam objective).

I have curated a list of articles from Microsoft documentation for each objective of the DA-100 exam. I hope this article will help you to achieve the Microsoft Certified Data Analyst Associate Certificate. Also, please share the post within your circles so it helps them to prepare for the exam.

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DA-100 Analyzing Data with Microsoft Power BI

DA-100 Microsoft Power BI Practice Test

Microsoft Power BI Projects

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Using DA-100 exam dumps can get you permanently banned from taking any future Microsoft certificate exam. Read the FAQ page for more information. However, I strongly suggest you validate your understanding with practice questions.

DA-100 Sample Practice Exam Questions

DA-100 Microsoft Power BI Exam Tips

  • Lots of questions on use cases (15-16 questions out of 57)
  • Exam very DAX intensive. Practice exercises a lot (around 17-19 questions)
  • Lots of questions on power BI service, apps publishing & distribution

Other topics include:

      • M query writing, data cleansing, and transformation
      • Questions on concepts related to drilling through functionality, filtering, all kinds of joins, & cardinality.

Full Disclosure: Some of the links in this post are affiliate links. I receive a commission when you purchase through them.

Prepare the Data (20-25%)

Get Data from Different Data Sources

Identify and connect to a data source

Data sources in Power BI desktop

Connect to data in Power BI desktop

Change data source settings

Manage data sources

Select a shared dataset or create a local dataset

Where your workbook file is saved makes a difference

Power BI shared datasets

Select a storage mode

Storing data in the Power BI file

Choose an appropriate query type

Query overview in Power BI Desktop

Identify query performance issues

Fix performance issues

Optimization guide for Power BI

Use Microsoft Dataverse

What is Microsoft Dataverse?

Get started with Dataverse

Use parameters

Specify parameters for the data source in Power BI

Use or create a PBIDS file

Using PBIDS files to get data

How to create a PBIDS connection file?

Use or create a data flow

Creating a dataflow

Connect to a dataset using the XMLA endpoint

Dataset connectivity with the XMLA endpoint

Profile the Data

Clean, Transform, and Load the Data

Resolve inconsistencies, unexpected or null values, and data quality issues

Inconsistencies with date-type fields

Tips & tricks for creating relationships in Power BI Desktop

Relationships in Power BI Desktop when the data has null or blank values

How to Spot and Improve Data Quality in Power BI

Apply user-friendly value replacements

Replace Values and Column Data Types with Power BI

Replacing the values

Identify and create appropriate keys for joins

Model relationships in Power BI Desktop

Evaluate and transform column data types

Evaluate & change column data types

Apply data shape transformations to table structures

Shape & combine data in Power BI Desktop

Combine queries

Merging queries

Apply user-friendly naming conventions to columns and queries

Data import best practices in Power BI

Leverage Advanced Editor to modify Power Query M code

The Advanced Editor

Configure data loading

New updates in Power Query

Resolve data import errors

Resolve data import errors

DA-100 Introducing Microsoft Power BI

Amazon link (affiliate)

Model the Data (25-30%)

Design a Data Model

Define the tables

Tables in Power BI reports and dashboards

Configure table and column properties

Format the table

Adjust the column width of a table

Define quick measures

Use quick measures for common calculations

Flatten out a parent-child hierarchy

Video on flattening a parent-child hierarchy

Define role-playing dimensions

Role-playing dimensions

Define a relationship’s cardinality and cross-filter direction

The Cardinality option

Cross filter direction

Design the data model to meet performance requirements

Optimization guide for Power BI

Resolve many-to-many relationships

Many-to-many relationship guidance

Create a common date table

Common Date Filter for Multiple Tables

Define the appropriate level of data granularity

Hierarchies in data models

Develop a Data Model

Create Measures by Using DAX

Use DAX to build complex measures

Create & use your own measures

DAX: Use variables to improve your formulas

Use CALCULATE to manipulate filters

DAX: Avoid using FILTER as a filter argument

Implement Time Intelligence using DAX

Time intelligence in Power BI desktop

Replace numeric columns with measures

Convert column to measure

Use basic statistical functions to enhance data

DAX Statistical Functions

Create semi-additive measures

Semi additive measures in DAX for Power pivot

Optimize Model Performance

Remove unnecessary rows and columns

Delete records or rows if the blank field

Remove Columns from Tables in Power BI

Identify poorly performing measures, relationships, and visuals

Slow Measures

Dealing with slow measures

Slow Power BI report

Table relationship causes severe performance drop

Power BI Desktop Visuals slow load

Improve cardinality levels by changing data types

Optimize high cardinality columns in VertiPaq

Improve cardinality levels through summarization

Summarizing data

Create and manage aggregations

Create & manage aggregations

Visualize the Data (20-25%)

Create Reports

Add visualization items to reports

Add visuals to a Power BI report

Choose an appropriate visualization type

Visualization types in Power BI

Format and configure visualizations

Getting started with the formatting pane

Import a custom visual

Power BI visual files

Configure conditional formatting

Use conditional formatting in tables

Apply slicing and filtering

Slicers in Power BI

Add a filter to a report in Power BI

Add an R or Python visual

Create Power BI visuals by using Python

Create Power BI visuals using R

Configure the report page

Change the display of a report page

Design and configure for accessibility

Design Power BI reports for accessibility

Configure automatic page refresh

Automatic page refresh in Power BI

Create a paginated report

What are paginated reports?

Create a paginated report for Power BI Report Server

Create a paginated report based on a Power BI shared dataset

Create Dashboards

Enrich Reports for Usability

Configure bookmarks

Bookmarks in Power BI desktop to share insights & build stories

Create custom tooltips

Customize tooltips in Power BI desktop

Edit and configure interactions between visuals

Change how visuals interact in a Power BI report

Configure navigation for a report

Make navigation easier with Power BI buttons

Apply sorting

Sort by column in Power BI Desktop

Configure Sync Slicers

Sync & use slicers on other pages

Use the selection pane

Power BI: Explore the new selection pane feature

Use drill through and cross filter

Set up drill through in Power BI reports

Drilldown into data using interactive visuals

Drill mode in a visual in Power BI

Export report data

Export data from a visual in a report

Design reports for mobile devices

Optimize Power BI reports for the mobile app

Power BI Design for Mobile Device

Analyze the Data (10-15%)

Enhance Reports to Expose Insights

Apply conditional formatting

Use conditional formatting in tables

Apply slicers and filters

Power BI Slicers vs Filters

Perform top N analysis

When & How to Use TOPN in Power BI

Explore statistical summary

Explore statistical summary

Use the Q&A visual

The Q&A feature in Power BI

Add a Quick Insights result to a report

Review Quick insights

Create reference lines by using the Analytics pane

Use the Analytics pane

Use the Play Axis feature of a visualization

Play Axis (Dynamic Slicer)

Personalize visuals

Let users personalize visuals in a report

Personalize visuals in a report

Perform Advanced Analysis

Identify outliers

Identify outliers with Power BI visuals

How to detect anomalies & outliers In your data

Conduct Time Series analysis

Conduct time series analysis

Use groupings and binnings

Use grouping and binning in Power BI desktop

Use the Key Influencers to explore dimensional variances

Find important factors with the Key influencers visual

Use the decomposition tree visual to break down a measure

Decomposition Tree visual to break down a measure

Apply AI Insights

Use AI insights in Power BI desktop

Deploy and Maintain Deliverables (10-15%)

Manage Datasets

Configure a dataset scheduled refresh

Configure scheduled refresh

Configure row-level security group membership

Power BI Row-level Security Groups

Row-level security using AD groups

Providing access to datasets

Build permission for shared datasets

Configure incremental refresh settings

Incremental refresh in Power BI

Promote or certify Power BI datasets

Promote your dataset – Power BI

Certify datasets – Power BI

Identify downstream dataset dependencies

Dataset impact analysis

Configure large dataset format

Large datasets in Power BI Premium

Using Power BI with large datasets

Create and Manage Workspaces

This brings us to the end of the DA-100 Analyzing Data with Microsoft Power BI Study Guide.

What do you think? Let me know in the comments section if I have missed out on anything. Also, I love to hear from you about how your preparation is going on!

In case you are preparing for other Power Platform certification exams, check out the Power Platform study guides for those exams.

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