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Microsoft Power BI

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  • Design and build scalable data models
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Date Time Course Type Price Option
Microsoft Power BI is a power full Data Analysts application that enable businesses to maximize the value of their data assets. As a subject matter expert, data analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. 

Prepare the Data (20-25%)  
Model the Data
Develop a data model
Create measures by using DAX
Visualize the Data (20-25%)
Analyze the Data (10-15%)
Deploy and Maintain Deliverables (10-15%)
Prepare the Data (20-25%)
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
• Use Microsoft Dataverse
• Use parameters
• Use or create a PBIDS file
• Use or create a data flow
• Connect to a dataset using the XMLA endpoint
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 (25-30%)
Design a data model
• 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
• create a common date table
• define the appropriate level of data granularity
Develop a data model
• apply cross-filter direction and security filtering
• create calculated tables
• create hierarchies
• create calculated columns
• implement row-level security roles
• implement object-level security
• set up the Q&A feature
Create measures by using DAX
• use DAX to build complex measures
• use CALCULATE to manipulate filters
• implement Time Intelligence using DAX
• 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
• use Query Diagnostics
Visualize the Data (20-25%)
Create reports
• add visualization items to reports
• choose an appropriate visualization type
• format and configure visualizations
• import a custom visual
• configure conditional formatting
• apply slicing and filtering
• add an R or Python visual
• configure the report page
• design and configure for accessibility
• configure automatic page refresh
• create a paginated report
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
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
• use drill through and cross filter
• drilldown into data using interactive visuals
• export report data
• design reports for mobile devices
Analyze the Data (10-15%)
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 Analytics pane
• use the Play Axis feature of a visualization
• personalize visuals
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 (10-15%)
Manage datasets
• configure a dataset scheduled refresh
• configure row-level security group membership
• provide access to datasets
• configure incremental refresh settings
• promote or certify Power BI datasets
• identify downstream dataset dependencies
• configure large dataset format
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
• use deployment pipelines
• configure subscriptions
• promote or certify Power BI content
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