MICROSOFT POWER BI DA-100 EXAM TESTS 2022

Description

Analyzing Data with Microsoft Power BI DA-100

Topics :

six knowledge areas:

• Microsoft DAX language;
• Microsoft Power Query features;
• Data Modeling in Power BI;
• Data Visualization in Power BI;
• Manage Publishing and Sharing Power BI contents;
• Manage Power BI Administration settings.

Prepare the Data

Get data from different data sources

• identify and connect to a data source
• change data source settings
• select a shared dataset or create a local dataset
• select a storage mode
• choose an appropriate query type
• identify query performance issues

Profile the data

• identify data anomalies
• examine data structures
• interrogate column properties
• interrogate data statistics

Clean, transform and load the data

• resolve inconsistencies, unexpected or null values, and data quality issues
• apply user-friendly value replacements
• identify and create appropriate keys for joins
• evaluate and transform column data types
• apply data shape transformations to table structures
• combine queries
• apply user-friendly naming conventions to columns and queries
• leverage Advanced Editor to modify Power Query M code
• configure data loading
• resolve data import errors

Model the Data

• define the tables
• configure table and column properties
• define quick measures
• flatten out a parent-child hierarchy
• define role-playing dimensions
• define a relationship’s cardinality and cross-filter direction
• design the data model to meet performance requirements
• resolve many-to-many relationships

Develop a data model

• apply cross-filter direction and security filtering
• create calculated tables
• create hierarchies
• create calculated columns
• implement row-level security roles
• set up the Q&A feature

Create measures by using DAX

• use DAX to build complex measures
• use CALCULATE to manipulate filters
• replace numeric columns with measures
• use basic statistical functions to enhance data
• create semi-additive measures

Optimize model performance

• remove unnecessary rows and columns
• identify poorly performing measures, relationships, and visuals
• improve cardinality levels by changing data types
• improve cardinality levels through summarization
• create and manage aggregations

Visualize the Data

• add visualization items to reports
• choose an appropriate visualization type
• format and configure visualizations
• import a custom visual
• configure the report page
• design and configure for accessibility
• configure automatic page refresh

Create dashboards

• set mobile view
• manage tiles on a dashboard
• configure data alerts
• use the Q&A feature
• add a dashboard theme
• pin a live report page to a dashboard
• configure data classification

Enrich reports for usability

• configure bookmarks
• create custom tooltips
• edit and configure interactions between visuals
• configure navigation for a report
• apply sorting
• configure Sync Slicers
• use the selection pane

Analyze the Data

Enhance reports to expose insights

• apply conditional formatting
• apply slicers and filters
• perform top N analysis
• explore statistical summary
• use the Q&A visual
• add a Quick Insights result to a report
• create reference lines by using the Analytics pane

Perform advanced analysis

• identify outliers
• conduct Time Series analysis
• use groupings and binnings
• use the Key Influencers to explore dimensional variances
• use the decomposition tree visual to break down a measure
• apply AI Insights

Deploy and Maintain Deliverables

Manage datasets

• configure a dataset scheduled refresh
• configure row-level security group membership
• providing access to datasets
• configure incremental refresh settings

Create and manage workspaces

• create and configure a workspace
• recommend a development lifecycle strategy
• assign workspace roles
• configure and update a workspace app
• publish, import, or update assets in a workspace
• apply sensitivity labels to workspace content