Power BI and SQL Database Training
Level
AdvancedDuration
24h / 3 daysDate
Individually arrangedPrice
Individually arrangedPower BI and SQL Database Training
This training is intended for people working with processing and analyzing large amounts of data, including analysts and decision-makers using SQL database data. The scope covers the use of SQL databases in combination with Microsoft Power BI. Databases may include Microsoft SQL Server, Azure SQL, IBM DB2, Informix, Oracle SQL, PostgreSQL, MySQL, MariaDB, or Microsoft Access.
What You Will Learn
- Efficiently acquire and process data for business decision-making
- Use PowerQuery and data preparation techniques
- Learn the terminology and tools necessary for extracting information from SQL databases and presenting it in Power BI
- Apply the DAX library for reporting and analysis
- Tell stories with data using visualization techniques
Who is this training for?
Analysts, marketers, and everyone working with data-
People processing and analyzing large datasets
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Those who want to learn the DAX library
Training Program
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Introduction to the Program
- Versions, license types, and features
- Main applications and user interface overview
- Reports, cards, and visualizations – key Power BI elements
- Cloud Power BI services – capabilities and limitations
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First Power BI Model
- Working with a single-table data model
- Basic visualizations and binding data to visuals
- Data types, conversions, and regional settings
- Line, bar, and scatter charts – formatting
- Card, table, and matrix visuals – formatting
- Geographic visualizations – maps and choropleths
- Visualization, card, and report-level filters
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Working with Multi-Table Models
- Tables, relationships, and data models
- Automatic and manual relationships
- Model optimization and modification
- Calculated columns and KPIs
- Introduction to data modeling and joins
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Power Query Data Model for Power BI Desktop
- Data source types – capabilities and limitations
- Flat files (CSV, JSON) and folder-based sources
- Spreadsheet data as a visualization source
- Combining custom data sources: SQL, CSV, Web
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Advanced Visual Elements
- Key Performance Indicators (KPIs)
- Advanced hierarchies in data models
- Custom visuals from marketplace and files
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Sharing Power BI Desktop Reports
- Exporting data to CSV
- Exporting reports to PDF
- Publishing reports to the cloud
- Embedding reports in SharePoint and public websites
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Data Processing Stages in Power BI
- SQL query execution
- Data transformation using M language
- DAX processing layer
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SQL Databases – Introduction and Overview
- SQL database concepts
- SQL language categories: DQL, DML, DDL, DCL
- Connecting to SQL servers and databases
- SQL editors and development tools
- Server objects: tables, views, stored procedures
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Connecting Power BI to a Database
- Direct database connections
- ODBC connections
- Loading data from tables and views
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Power Query for Data Transformation
- Filtering and sorting data
- Calculated and conditional columns
- Custom column creation
- Text and mathematical functions
- Data type conversions
- Merging and splitting columns
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Data Model and M Language
- Appending and merging tables
- Relationships and Excel-based models
- Advanced M language functions
- Removing duplicates
- Pivot and unpivot operations
- Aggregations and counts
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Practical Aspects of the Data Model
- Pivot tables based on the data model
- Multiple object references
- Data refresh mechanisms
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Introduction to DAX
- What DAX is and where it is used
- Requirements and prerequisites
- Work environment: formula bar and calculation area
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Working with DAX
- DAX syntax
- Calculated columns and use cases
- Formula structure and formatting
- Measures in DAX
- Auto-sum functionality
- Functions and function types
- RELATED and relationship functions
- Row context and filter context
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DQL – Data Query Language
- Using Query Designer
- SQL data types and usage
- SQL data standards
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SELECT Statement
- SELECT statement syntax
- Logical execution order of SELECT
