*COURSE DETAILS* :
*COURSE DETAILS* :
Training type | Instructor-led Online |
---|---|
Facilities | Industry Expert Trainer | 24*7 Virtual Lab Access | Study Materials |
Batch Strength | 10 |
Timings | 2 – 4 Hours in a day |
Duration | 40 Hours |
Fee | $18.05 |
Upcoming | Upcoming Class |
Course overview
Skills measured
- Implement and manage a data analytics environment (25–30%)
- Query and transform data (20–25%)
- Implement and manage data models (25–30%)
- Explore and visualize data (20–25%)
Functional groups
Implement and manage a data analytics environment (25–30%)
Govern and administer a data analytics environment
- Manage Power BI assets by using Azure Purview
- Identify data sources in Azure by using Azure Purview
- Recommend settings in the Power BI admin portal
- Recommend a monitoring and auditing solution for a data analytics environment, including Power BI REST API and PowerShell cmdlets
Integrate an analytics platform into an existing IT infrastructure
- Identify requirements for a solution, including features, performance, and licensing strategy
- Configure and manage Power BI capacity
- Recommend and configure an on-premises gateway in Power BI
- Recommend and configure a Power BI tenant or workspace to integrate with Azure Data Lake Storage Gen2
- Integrate an existing Power BI workspace into Azure Synapse Analytics
Manage the analytics development lifecycle
- Commit code and artifacts to a source control repository in Azure Synapse Analytics
- Recommend a deployment strategy for Power BI assets
- Recommend a source control strategy for Power BI assets
- Implement and manage deployment pipelines in Power BI
- Perform impact analysis of downstream dependencies from dataflows and datasets
- Recommend automation solutions for the analytics development lifecycle, including Power BI REST API and PowerShell cmdlets
- Deploy and manage datasets by using the XMLA endpoint
- Create reusable assets, including Power BI templates, Power BI data source (.pbids) files, and
shared datasets
Query and transform data (20–25%)
Query data by using Azure Synapse Analytics
- Identify an appropriate Azure Synapse pool when analyzing data
- Recommend appropriate file types for querying serverless SQL pools
- Query relational data sources in dedicated or serverless SQL pools, including querying partitioned data sources
- Use a machine learning PREDICT function in a query
Ingest and transform data by using Power BI
- Identify data loading performance bottlenecks in Power Query or data sources
- Implement performance improvements in Power Query and data sources
- Create and manage scalable Power BI dataflows
- Identify and manage privacy settings on data sources
- Create queries, functions, and parameters by using the Power Query Advanced Editor
- Query advanced data sources, including JSON, Parquet, APIs, and Azure Machine Learning
models
Implement and manage data models (25–30%)
Design and build tabular models
- Choose when to use DirectQuery for Power BI datasets
- Choose when to use external tools, including DAX Studio and Tabular Editor 2
- Create calculation groups
- Write calculations that use DAX variables and functions, for example handling blanks or errors, creating virtual relationships, and working with iterators
- Design and build a large format dataset
- Design and build composite models, including aggregations
- Design and implement enterprise-scale row-level security and object-level security
Optimize enterprise-scale data models
- Identify and implement performance improvements in queries and report visuals
- Troubleshoot DAX performance by using DAX Studio
- Optimize a data model by using Tabular Editor 2
- Analyze data model efficiency by using VertiPaq Analyzer
- Implement incremental refresh
- Optimize a data model by using denormalization
Explore and visualize data (20–25%)
Explore data by using Azure Synapse Analytics
- Explore data by using native visuals in Spark notebooks
- Explore and visualize data by using the Azure Synapse SQL results pane
Visualize data by using Power BI
- Create and import a custom report theme
- Create R or Python visuals in Power BI
- Connect to and query datasets by using the XMLA endpoint
- Design and configure Power BI reports for accessibility
- Enable personalized visuals in a report
- Configure automatic page refresh
- Create and distribute paginated reports in Power BI Report Builder
- 24*7 Lab Access
- Online Training
- Instructor-led Training
- One-to-one Sessions
- Advanced Lab Equipments