[New] 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
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