Analyzing Data with Microsoft Power BI Practice Test

DA-100 test Format | Course Contents | Course Outline | test Syllabus | test Objectives

Exam Number : DA-100
Exam Name : Analyzing Data with Microsoft Power BI

This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Finally, this course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI.

Skills Gained
- Ingest, clean, and transform data
- Model data for performance and scalability
- Design and create reports for data analysis
- Apply and perform advanced report analytics
- Manage and share report assets
- Create paginated reports in Power BI

Specifically:
- Understanding core data concepts.
- Knowledge of working with relational data in the cloud.
- Knowledge of working with non-relational data in the cloud.
- Knowledge of data analysis and visualization concepts.

Course outline
Module 1: Get Started with Microsoft Data Analytics
This module explores the different roles in the data space, outlines the important roles and responsibilities of a Data Analysts, and then explores the landscape of the Power BI portfolio.

Lessons
Data Analytics and Microsoft
Getting Started with Power BI
Lab : Getting Started
Getting Started
After completing this module, you will be able to:

Explore the different roles in data
Identify the tasks that are performed by a data analyst
Describe the Power BI landscape of products and services
Use the Power BI service
Module 2: Prepare Data in Power BI
This module explores identifying and retrieving data from various data sources. You will also learn the options for connectivity and data storage, and understand the difference and performance implications of connecting directly to data vs. importing it.

Lessons
Get data from various data sources
Optimize performance
Resolve data errors
Lab : Preparing Data in Power BI Desktop
Prepare Data

After completing this module, you will be able to:

Identify and retrieve data from different data sources
Understand the connection methods and their performance implications
Optimize query performance
Resolve data import errors
Module 3: Clean, Transform, and Load Data in Power BI
This module teaches you the process of profiling and understanding the condition of the data. They will learn how to identify anomalies, look at the size and shape of their data, and perform the proper data cleaning and transforming steps to prepare the data for loading into the model.

Lessons
Data shaping
Enhance the data structure
Data Profiling
Lab : Transforming and Loading Data
Loading Data

After completing this module, students will be able to:

Apply data shape transformations
Enhance the structure of the data
Profile and examine the data
Module 4: Design a Data Model in Power BI
This module teaches the fundamental concepts of designing and developing a data model for proper performance and scalability. This module will also help you understand and tackle many of the common data modeling issues, including relationships, security, and performance.

Lessons
Introduction to data modeling
Working with tables
Dimensions and Hierarchies
Lab : Data Modeling in Power BI Desktop
Create Model Relationships
Configure Tables
Review the model interface
Create Quick Measures
Lab : Advanced Data Modeling in Power BI Desktop
Configure many-to-many relationships
Enforce row-level security

After completing this module, you will be able to:

Understand the basics of data modeling
Define relationships and their cardinality
Implement Dimensions and Hierarchies
Create histograms and rankings
Module 5: Create Model Calculations using DAX in Power BI
This module introduces you to the world of DAX and its true power for enhancing a model. You will learn about aggregations and the concepts of Measures, calculated columns and tables, and Time Intelligence functions to solve calculation and data analysis problems.

Lessons
Introduction to DAX
DAX context
Advanced DAX
Lab : Introduction to DAX in Power BI Desktop
Create calculated tables
Create calculated columns
Create measures
Lab : Advanced DAX in Power BI Desktop
Use the CALCULATE() function to manipulate filter context
use Time Intelligence functions

After completing this module, you will be able to:

Understand DAX
Use DAX for simple formulas and expressions
Create calculated tables and measures
Build simple measures
Work with Time Intelligence and Key Performance Indicators
Module 6: Optimize Model Performance
In this module you are introduced to steps, processes, concepts, and data modeling best practices necessary to optimize a data model for enterprise-level performance.

Lessons
Optimze the model for performance
Optimize DirectQuery Models
Create and manage Aggregations

After completing this module, you will be able to:

Understand the importance of variables
Enhance the data model
Optimize the storage model
Implement aggregations
Module 7: Create Reports
This module introduces you to the fundamental concepts and principles of designing and building a report, including selecting the correct visuals, designing a page layout, and applying basic but critical functionality. The important syllabu of designing for accessibility is also covered.

Lessons
Design a report
Enhance the report
Lab : Designing a report in Power BI
Create a live connection in Power BI Desktop
Design a report
Configure visual fields adn format properties
Lab : Enhancing Power BI reports with interaction and formatting
Create and configure Sync Slicers
Create a drillthrough page
Apply conditional formatting
Create and use Bookmarks

After completing this module, you will be able to:

Design a report page layout
Select and add effective visualizations
Add basic report functionality
Add report navigation and interactions
Improve report performance
Design for accessibility
Module 8: Create Dashboards
In this module you will learn how to tell a compelling story through the use of dashboards and the different navigation tools available to provide navigation. You will be introduced to features and functionality and how to enhance dashboards for usability and insights.

Lessons
Create a Dashboard
Real-time Dashboards
Enhance a Dashboard
Lab : Designing a report in Power BI Desktop - Part 1
Create a Dashboard
Pin visuals to a Dashboard
Configure a Dashboard tile alert
Use Q&A to create a dashboard tile

After completing this module, students will be able to:

Create a Dashboard
Understand real-time Dashboards
Enhance Dashboard usability
Module 9: Create Paginated Reports in Power BI
This module will teach you about paginated reports, including what they are how they fit into Power BI. You will then learn how to build and publish a report.

Lessons
Paginated report overview
Create Paginated reports
Lab : Creating a Paginated report
Use Power BI Report Builder
Design a multi-page report layout
Define a data source
Define a dataset
Create a report parameter
Export a report to PDF

After completing this module, you will be able to:

Explain paginated reports
Create a paginated report
Create and configure a data source and dataset
Work with charts and tables
Publish a report
Module 10: Perform Advanced Analytics
This module helps you apply additional features to enhance the report for analytical insights in the data, equipping you with the steps to use the report for genuine data analysis. You will also perform advanced analytics using AI visuals on the report for even deeper and meaningful data insights.

Lessons
Advanced Analytics
Data Insights through AI visuals
Lab : Data Analysis in Power BI Desktop
Create animated scatter charts
Use teh visual to forecast values
Work with Decomposition Tree visual
Work with the Key Influencers visual

After completing this module, you will be able to:

Explore statistical summary
Use the Analyze feature
Identify outliers in data
Conduct time-series analysis
Use the AI visuals
Use the Advanced Analytics custom visual
Module 11: Create and Manage Workspaces
This module will introduce you to Workspaces, including how to create and manage them. You will also learn how to share content, including reports and dashboards, and then learn how to distribute an App.

Lessons
Creating Workspaces
Sharing and Managing Assets
Lab : Publishing and Sharing Power BI Content
Map security principals to dataset roles
Share a dashboard
Publish an App

After completing this module, you will be able to:

Create and manage a workspace
Understand workspace collaboration
Monitor workspace usage and performance
Distribute an App
Module 12: Manage Datasets in Power BI
In this module you will learn the concepts of managing Power BI assets, including datasets and workspaces. You will also publish datasets to the Power BI service, then refresh and secure them.

Lessons
Parameters
Datasets

After completing this module, you will be able to:

Create and work with parameters
Manage datasets
Configure dataset refresh
Troubleshoot gateway connectivity
Module 13: Row-level security
This module teaches you the steps for implementing and configuring security in Power BI to secure Power BI assets.

Lessons
Security in Power BI

After completing this module, you will be able to:

Understand the aspects of Power BI security
Configure row-level security roles and group memberships

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DA-100
Analyzing Data with Microsoft Power BI
https://killexams.com/pass4sure/exam-detail/DA-100
Question: 221
You have a prospective customer list that contains 1,500 rows of data.
The list contains the following fields:
� First name
� Last name
� Email address
� State/Region
� Phone number
You import the list into Power Query Editor.
You need to ensure that the list contains records for each State/Region to which you want to target a marketing
campaign.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct
selection is worth one point.
A . Open the Advanced Editor.
B . Select Column quality.
C . Enable Column profiling based on entire dataset.
D . Select Column distribution.
E . Select Column profile.
Answer: DE
Explanation:
Data Profiling, Quality & Distribution in Power BI / Power Query features
To enable these features, you need to go to the View tab � Data Preview Group � Check the following:
� Column quality
� Column profile
� Column distribution
� Column profile
Turn on the Column Profiling feature.
� Column distribution
Can use it to visually realize that your query is missing some data because of distinct and uniqueness counts.
Reference:
https://www.poweredsolutions.co/2019/08/13/data-profiling-quality-distribution-in-power-bi-power-query/
https://www.altentertraining.com/microsoft/power-bi/column-profiling-is-good/
Question: 222
You open a query in Power Query Editor.
You need to identify the percentage of empty values in each column as quickly as possible.
Which Data Preview option should you select?
A . Show whitespace
B . Column profile
C . Column distribution
D . Column quality
Answer: D
Explanation:
Column quality: In this section, we can easily see valid, Error and Empty percentage of data values associated with the
Selected table.
Note: In Power Query Editor, Under View tab in Data Preview Section we can see the following data profiling
functionalities:
� Column quality
� Column distribution
� Column profile
Reference: https://community.powerbi.com/t5/Community-Blog/Data-Profiling-in-Power-BI-Power-BI-Update-April-
2019/ba-p/674555
Question: 223
DRAG DROP
You are building a dataset from a JSON file that contains an array of documents.
You need to import attributes as columns from all the documents in the JSON file. The solution must ensure that date
attributes can be used as date hierarchies in Microsoft Power BI reports.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions
to the answer area and arrange them in the correct order.
Answer:
Explanation:
Step 1: Expand the records.
First Open Power BI desktop and navigate to Power Query, import the JSON file, then load the data, click on the
record to expand it and to see the record and list.
Step 2: Add columns that use data type conversions.
Step 3: Convert the list to a table
Question: 224
You have the tables shown in the following table.
The Impressions table contains approximately 30 million records per month.
You need to create an ad analytics system to meet the following requirements:
� Present ad impression counts for the day, campaign, and Site_name. The analytics for the last year are required.
� Minimize the data model size.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct
selection is worth one point.
A . Group the impressions by Ad_id, Site_name, and Impression_date. Aggregate by using the CountRows function.
B . Create one-to-many relationships between the tables.
C . Create a calculated measure that aggregates by using the COUNTROWS function.
D . Create a calculated table that contains Ad_id, Site_name, and Impression_date.
Answer: AB
Explanation:
Question: 225
Your company has training videos that are published to Microsoft Stream. You need to surface the videos directly in a
Microsoft Power BI dashboard.
Which type of tile should you add?
A . video
B . custom streaming data
C . text box
D . web content
Answer: B
Explanation:
The only way to visualize a streaming dataset is to add a tile and use the streaming dataset as a custom streaming data
source.
Reference: https://docs.microsoft.com/en-us/power-bi/connect-data/service-real-time-streaming
Question: 226
Testlet 1
Case Study
This is a case study. Case studies are not timed separately. You can use as much test time as you would like to
complete each case. However, there may be additional case studies and sections on this exam. You must manage your
time to ensure that you are able to complete all question included on this test in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case
study. Case studies might contain exhibits and other resources that provide more information about the scenario that is
described in the case study. Each question is independent of the other question on this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make
changes before you move to the next section of the exam. After you begin a new section, you cannot return to this
section.
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to explore the
content of the case study before you answer the questions. Clicking these buttons displays information such as
business requirements, existing environment, and problem statements. If the case study has an All Information tab ,
note that the information displayed is identical to the information displayed on the subsequent tabs. When you are
ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. is an online retailer that uses Microsoft Power BI dashboards and reports.
The company plans to leverage data from Microsoft SQL Server databases, Microsoft Excel files, text files, and
several other data sources.
Litware uses Azure Active Directory (Azure AD) to authenticate users.
Existing Environment
Sales Data
Litware has online sales data that has the SQL schema shown in the following table.
In the Date table, the date_id column has a format of yyyymmdd and the month column has a format of yyyymm.
The week column in the Date table and the week_id column in the Weekly_Returns table have a format of yyyyww.
The region_id column can be managed by only one sales manager.
Sales Data
Litware, Inc. is an online retailer that uses Microsoft Power BI dashboards and reports.
The company plans to leverage data from Microsoft SQL Server databases, Microsoft Excel files, text files, and
several other data sources.
Litware uses Azure Active Directory (Azure AD) to authenticate users.
Data Concerns
You are concerned with the quality and completeness of the sales data. You plan to verify the sales data for negative
sales amounts.
Reporting Requirements
Litware identifies the following technical requirements:
� Executives require a visual that shows sales by region.
� Region managers require a visual to analyze weekly sales and returns.
� Sales managers must be able to see the sales data of their respective region only.
� The sales managers require a visual to analyze sales performance versus sales targets.
� The sale department requires reports that contain the number of sales transactions.
� Users must be able to see the month in reports as shown in the following example: Feb 2020.
� The customer service department requires a visual that can be filtered by both sales month and ship month
independently.
You need to create a calculated column to display the month based on the reporting requirements.
Which DAX expression should you use?
A . FORMAT(�Date'[date], "MMM YYYY")
B . FORMAT(�Date� [date], "M YY")
C . FORMAT(�Date'[date_id], "MMM") & "" & FORMAT(�Date'[year], "#")
D . FORMAT(�Date� [date_id], "MMM YYYY")
Answer: D
Explanation:
Scenario: In the Date table, the date_id column has a format of yyyymmdd. Users must be able to see the month in
reports as shown in the following example: Feb 2020.
Question: 228
Question Set 3
You have a large dataset that contains more than 1 million rows. The table has a datetime column named Date.
You need to reduce the size of the data model.
What should you do?
A . Round the hour of the Date column to startOfHour.
B . Change the data type of the Date column to Text.
C . Trim the Date column.
D . Split the Date column into two columns, one that contains only the time and another that contains only the date.
Answer: D
Explanation:
We have to separate date & time tables. Also, we don’t need to put the time into the date table, because the time is
repeated every day. Split your DateTime column into a separate date & time columns in fact table, so that you can join
the date to the date table & the time to the time table. The time need to be converted to the nearest round minute or
second so that every time in your data corresponds to a row in your time table.
Reference: https://intellipaat.com/community/6461/how-to-include-time-in-date-hierarchy-in-power-bi
Question: 229
You have a data model that contains many complex DAX expressions. The expressions contain frequent references to
the RELATED and RELATEDTABLE functions.
You need to recommend a solution to minimize the use of the RELATED and RELATEDTABLE functions.
What should you recommend?
A . Split the model into multiple models.
B . Hide unused columns in the model.
C . Merge tables by using Power Query.
D . Transpose.
Answer: C
Explanation:
Combining data means connecting to two or more data sources, shaping them as needed, then consolidating them into a
useful query. When you have one or more columns that you’d like to add to another query, you merge the queries.
Note: The RELATEDTABLE function is a shortcut for CALCULATETABLE function with no logical expression.
CALCULATETABLE evaluates a table expression in a modified filter context and returns A table of values.
Reference: https://docs.microsoft.com/en-us/power-bi/connect-data/desktop-shape-and-combine-data
Question: 230
You have the following three versions of an Azure SQL database:
� Test
� Production
� Development
You have a dataset that uses the development database as a data source.
You need to configure the dataset so that you can easily change the data source between the development, test, and
production database servers from powerbi.com.
Which should you do?
A . Create a JSON file that contains the database server names. Import the JSON file to the dataset.
B . Create a parameter and update the queries to use the parameter.
C . Create a query for each database server and hide the development tables.
D . Set the data source privacy level to Organizational and use the ReplaceValuePower Query M function.
Answer: D
Explanation:
With privacy level settings, you can specify an isolation level that defines the degree that one data source must be
isolated from other data sources.
An Organizational data source limits the visibility of a data source to a trusted group of people. An Organizational data
source is isolated from all Public data sources, but is visible to other Organizational data sources.
Reference: https://docs.microsoft.com/en-us/power-bi/admin/desktop-privacy-levels
Question: 231
You have an Azure SQL database that contains sales transactions. The database is updated frequently.
You need to generate reports from the data to detect fraudulent transactions. The data must be visible within five
minutes of an update.
How should you configure the data connection?
A . Add a SQL statement.
B . Set Data Connectivity mode to DirectQuery.
C . Set the Command timeout in minutes setting.
D . Set Data Connectivity mode to Import.
Answer: B
Explanation:
With Power BI Desktop, when you connect to your data source, it�s always possible to import a copy of the data into
the Power BI Desktop. For some data sources, an alternative approach is available: connect directly to the data source
using DirectQuery.
DirectQuery: No data is imported or copied into Power BI Desktop. For relational sources, the selected tables and
columns appear in the Fields list. For multi-dimensional sources like SAP Business Warehouse, the dimensions and
measures of the selected cube appear in the Fields list. As you create or interact with a visualization, Power BI
Desktop queries the underlying data source, so you’re always viewing current data.
Incorrect Answers:
D: Import: The selected tables and columns are imported into Power BI Desktop. As you create or interact with a
visualization, Power BI Desktop uses the imported data. To see underlying data changes since the initial import or the
most latest refresh, you must refresh the data, which imports the full dataset again.
Reference: https://docs.microsoft.com/en-us/power-bi/connect-data/desktop-use-directquery
Question: 232
Testlet 2
Case Study
This is a case study. Case studies are not timed separately. You can use as much test time as you would like to
complete each case. However, there may be additional case studies and sections on this exam. You must manage your
time to ensure that you are able to complete all questions included on this test in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case
study. Case studies might contain exhibits and other resources that provide more information about the scenario that is
described in the case study. Each question is independent of the other question on this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make
changes before you move to the next section of the exam. After you begin a new section, you cannot return to this
section.
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to explore the
content of the case study before you answer the questions. Clicking these buttons displays information such as
business requirements, existing environment, and problem statements. If the case study has an All Information tab ,
note that the information displayed is identical to the information displayed on the subsequent tabs. When you are
ready to answer a question, click the Question button to return to the question.
Overview
Existing Environment
Contoso, Ltd. is a manufacturing company that produces outdoor equipment. Contoso has quarterly board meetings for
which financial analysts manually prepare Microsoft Excel reports, including profit and loss statements for each of the
company�s four business units, a company balance sheet, and net income projections for the next quarter.
Data and Sources
Data for the reports comes from three sources. Detailed revenue, cost, and expense data comes from an Azure SQL
database. Summary balance sheet data comes from Microsoft Dynamics 365 Business Central. The balance sheet data
is not related to the profit and loss results, other than they both relate dates.
Monthly revenue and expense projections for the next quarter come from a Microsoft SharePoint Online list. Quarterly
projections relate to the profit and loss results by using the following shared dimensions: date, business unit,
department, and product category.
Net Income Projection Data
Net income projection data is stored in a SharePoint Online list named Projections in the format shown in the
following table.
Revenue projections are set at the monthly level and summed to show projections for the quarter.
Balance Sheet Data
The balance sheet data is imported with final balances for each account per month in the format shown in the following
table.
There is always a row for each account for each month in the balance sheet data.
Dynamics 365 Business Central Data
Business Central contains a product catalog that shows how products roll up to product categories, which roll up to
business units.
Revenue data is provided at the date and product level. Expense data is provided at the date and department level.
Business Issues
Historically, it has taken two analysts a week to prepare the reports for the quarterly board meetings. Also, there is
usually at least one issue each quarter where a value in a report is wrong because of a bad cell reference in an Excel
formula. On occasion, there are conflicting results in the reports because the products and departments that roll up to
each business unit are not defined consistently.
Requirements
Planned Changes
Contoso plans to automate and standardize the quarterly reporting process by using Microsoft Power BI. The company
wants to how long it takes to populate reports to less than two days. The company wants to create common logic for
business units, products, and departments to be used across all reports, including, but not limited, to the quarterly
reporting for the board.
Technical Requirements
Contoso wants the reports and datasets refreshed with minimal manual effort.
The company wants to provide a single package of reports to the board that contains custom navigation and links to
supplementary information.
Maintenance, including manually updating data and access, must be minimized as much as possible.
Security Requirements
The reports must be made available to the board from powerbi.com. A mail-enabled security group will be used to
share information with the board.
The analysts responsible for each business unit must see all the data the board sees, except the profit and loss data,
which must be restricted to only their business unit�s data. The analysts must be able to build new reports from the
dataset that contains the profit and loss data, but any reports that the analysts build must not be included in the
quarterly reports for the board. The analysts must not be able to share the quarterly reports with anyone.
Report Requirements
You plan to relate the balance sheet to a standard date table in Power BI in a many-to-one relationship based on the
last day of the month. At least one of the balance sheet reports in the quarterly reporting package must show the
ending balances for the quarter, as well as for the previous quarter.
Projections must contain a column named RevenueProjection that contains the revenue projection amounts.
A relationship must be created from Projections to a table named Date that contains the columns shown in the
following table.
The relationships between products and departments to business units must be consistent across all reports.
The board must be able to get the following information from the quarterly reports:
� Revenue trends over time
� Ending balances for each account
� A comparison of expenses versus projections by quarter
� Changes in long-term liabilities from the previous quarter
� A comparison of quarterly revenue versus the same quarter during the prior year
What is the minimum number of datasets and storage modes required to support the reports?
A . two imported datasets
B . a single DirectQuery dataset
C . two DirectQuery datasets
D . a single imported dataset
Answer: A
Explanation:
Scenario: Data and Sources Data for the reports comes from three sources. Detailed revenue, cost, and expense data
comes from an Azure SQL database. Summary balance sheet data comes from Microsoft Dynamics 365 Business
Central. The balance sheet data is not related to the profit and loss results, other than they both relate dates.
Monthly revenue and expense projections for the next quarter come from a Microsoft SharePoint Online list. Quarterly
projections relate to the profit and loss results by using the following shared dimensions: date, business unit,
department, and product category.
Reference: https://docs.microsoft.com/en-us/power-bi/connect-data/service-datasets-understand
Question: 233
You import two Microsoft Excel tables named Customer and Address into Power Query.
Customer contains the following columns:
� Customer ID
� Customer Name
� Phone
� Email Address
� Address ID
Address contains the following columns:
� Address ID
� Address Line 1
� Address Line 2
� City
� State/Region
� Country
� Postal Code
The Customer ID and Address ID columns represent unique rows.
You need to create a query that has one row per customer. Each row must contain City, State/Region, and Country for
each customer.
What should you do?
A . Merge the Customer and Address tables.
B . Transpose the Customer and Address tables.
C . Group the Customer and Address tables by the Address ID column.
D . Append the Customer and Address tables.
Answer: A
Explanation:
There are two primary ways of combining queries: merging and appending.
� When you have one or more columns that you’d like to add to another query, you merge the queries.
� When you have additional rows of data that you’d like to add to an existing query, you append the query.
Reference: https://docs.microsoft.com/en-us/power-bi/connect-data/desktop-shape-and-combine-data

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