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Introduction to Power BI

 

Introduction to Power BI is a comprehensive workshop structured in modular format, allowing participants to tailor their learning experience based on

their specific needs. This program offers an in-depth exploration of Microsoft's dynamic business analytics tool, covering foundational elements and the integration with Excel. It emphasizes key components such as Pivot, Power Pivot, Power Query, DAX, and M, ensuring a thorough understanding of these tools.

Attendees will gain practical insights into building robust data models, with modules dedicated to Snowflake Schema, Star Schema, Fact Tables, and Dimension Tables. The course also focuses on the critical Extract, Transform, and Load (ETL) process, equipping participants with hands-on experience in data analysis and presentation techniques.

Throughout the workshop, participants will learn to create custom columns, measures, and calculated columns, enhancing their capabilities to extract meaningful insights from data. This flexible, module-based program is designed to empower individuals with the skills necessary to navigate Power BI's complexities and excel in data analysis, modeling, and presentation, catering to the diverse needs of clients.
 

Course Outline

The Anatomy of Power BI and Excel:

This section explores the relationship and integration between Power BI and Excel, detailing how they complement each other in data analysis and reporting. It may discuss importing Excel data into Power BI, leveraging Excel's calculation capabilities within Power BI, and how both tools can be used together for a comprehensive data solution.

 

Pivot:

Discusses the pivot feature, primarily within Excel, which allows users to reorganize and summarize complex datasets by rotating data axes and creating pivot tables for interactive data exploration.

 

Power Pivot:

An Excel add-in that enhances data analysis and modeling capabilities, allowing for large data sets integration, complex calculations, and creating sophisticated data models directly within Excel, which can then be utilized in Power BI.

 

Power Query:

A tool within Power BI (and Excel) used for data connection, transformation, and preparation. It enables users to easily connect to various data sources, clean and transform the data using a user-friendly interface before loading it into the model.

 

DAX (Data Analysis Expressions):

A formula language used within Power BI (and Power Pivot in Excel) for creating custom calculations and data analysis. DAX is used to extend data models with calculated columns, measures, and tables.

M:

The programming language behind Power Query for advanced data transformation and preparation tasks. It is used to script and automate data fetching, cleaning, and reshaping processes.

 

Custom Columns, Measures, and Calculated Columns:

This section would explain how to enhance data models in Power BI by adding custom columns (created through Power Query or DAX), measures (dynamic calculations used in reports), and calculated columns (columns computed from other data in the model).

 

Star Schema:

A simpler database schema used in data warehousing and business intelligence, including Power BI. It consists of a central fact table connected directly to dimension tables, ideal for performance and simplicity in data modeling.

 

Snowflake Schema:

A type of database schema that represents multidimensional data models, where the data is organized in a snowflake shape with fact tables linked to multiple dimensions, spreading out like a snowflake. It's useful for complex data models requiring normalization.

Fact Tables:

In data modeling, fact tables store quantitative information for analysis and reporting, typically Fact containing metrics and measures that can be aggregated. They are central in star and snowflake schemas.

 

Dimension Tables:

Tables in a data model that categorize and describe business entities—the dimensions of analysis—such as time, geography, or product. They are used to filter, group, and label data in fact tables.

 

Extract, Transform, and Load (ETL):

The process of extracting data from various sources, transforming it into a structured format, and loading it into a database or data warehouse for analysis. Power Query in Power BI is a tool that facilitates the ETL process.

 

Analysis:

This section would cover how Power BI is used to perform data analysis, including the use of DAX for creating measures and calculated columns, visualizing data through reports and dashboards, and deriving insights from data.

 

Presentation:

Discusses how to present data analysis and insights effectively using Power BI, including creating interactive reports and dashboards, custom visualizations, and sharing findings with stakeholders through Power BI service.

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