Azure Power BI (DA-100)

The course is intended for business analysts or data scientist looking to learn Microsoft Power BI. The course gives an overview of Azure and Power BI and talks about how to get the most of your data. It is designed as a crash course for those looking to get started with Microsoft Power BI and Azure.

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The course is intended for business analysts or data scientist looking to learn Microsoft Power BI. The course gives an overview of Azure and Power BI and talks about how to get the most of your data. It is designed as a crash course for those looking to get started with Microsoft Power BI and Azure.

Course content

 

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
  • 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
  • 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

 

To see the full course content Download now

Course Prerequisites

 
  • The Data Analyst should have a fundamental understanding of data repositories and data processing both on-premises and in the cloud.

Who can attend

 
  • Data Analyst looking to learn Power BI or get started with Azure
  • Data Sciences looking to build their skill set.
  • Anyone interested in learning best practices around reporting

Number of Hours: 40hrs

Certification

DA-100

Key features

  • One to One Training
  • Online Training
  • Fastrack & Normal Track
  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Virtual Live Experience
  • Preparing for Certification

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  • Materials
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