ALL STEPS OF DATA MODELING

 

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
  • 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

• 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
  • 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

Visualize the Data

• 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
  • 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
  • Use drillthrough and cross filter
  • Drilldown into data using interactive visuals
  • Export report data
  • Design reports for mobile devices

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 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

• Manage datasets
  • Configure a dataset scheduled refresh
  • Configure row-level security group membership
  • Providing access to datasets
  • Configure incremental refresh settings
  • Promote or certify Power BI content 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