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Power BI, a leading Business Intelligence tool, excels in facilitating decision-making with its versatile features. Seamlessly connecting to various data sources, including CRM and ERP, and integrating effortlessly with Microsoft products like Excel and Azure Cloud, Power BI offers an intuitive interface for dashboard creation. Data management is simplified through drag-and-drop functionality and natural language queries, with the added advantage of multiple daily data refreshes for real-time accuracy
Module 1: Introduction to Power BI Tools
Definition of Business Intelligence (BI)
Overview of Microsoft's Power BI solution
Power BI Desktop and Power BI Services
Power BI Desktop interface
Accessing the Power BI service
Introduction to technologies integrated into Power BI Desktop
Power BI report creation cycle
Power BI licenses
Module 2: Power Query - Creating Queries
Introduction to Power Query and its interface
Data mode
Applied steps principle
Obtaining data from various sources (Flat files, Excel, databases, Cloud, Web)
Essential applied steps for data transformation
Practical exercises, creating a query connected to an Excel file, and converting data types
Module 3: Power Query - Creating Queries (Continued)
Data cleaning techniques
Splitting or merging columns, cleaning spaces and field errors, replacing values
Adding custom columns using simple calculations and conditional expressions
Combining queries through merging or appending
Data refreshing and manual data entry
Practical exercises, creating a merged query from two queries, and creating a calculated column
Module 4: Building a Data Model
Vocabulary of relational models
Primary keys, foreign keys, relationships, and cardinalities
Relational approach in Power BI models
Star schema
Fact and dimension tables
Model view
Creating and managing relationships between tables
Introduction to DAX language for querying data
Creating calculated columns
Generating a date table in DAX
Practical exercises, creating relationships between tables, and creating a DAX-based date table
Module 5: Building a Data Model (Continued)
Creating measures
Concept of evaluation context
Essential DAX functions: RELATED, DIVIDE, IF, SWITCH, LEFT, RIGHT, YEAR, MONTH
Aggregation functions: SUM, AVERAGE, COUNTA
Iteration functions: SUMX, AVERAGEX, COUNTAX
Using quick measures for common calculations and initial Time Intelligence measures
Module 6: Creating Visualizations
Report view
Building visualizations
Data Visualization best practices
Choosing the right chart types
Tips for enhancing visual impact
Setting up comparison, distribution, and trend charts (Histograms, bars, rings, sectors, Treemap, curves)
Using visualizations to display data (Maps, tables, matrices)
Module 7: Creating Visualizations (Continued)
Displaying analyses with geographical data
Maps and choropleth maps
Exploring formatting features
Filter tools
Segments and filter pane
Synchronizing segments across pages and filter scope
Creating relative numeric and chronological filters
Key Performance Indicators (KPI)
KPI visualization
Conditional formatting
Interactive tools (Bookmarks, buttons)
Theme management
Inserting backgrounds, shapes, and images
Practical exercises, creating visual filters with segments, using tables and matrices for numerical analyses
Module 8: Sharing Visualizations on Power BI Site
Connecting and navigating the Power BI site
Workspace exploration
Introduction to user rights management
Understanding reports, dashboards, and datasets
Publishing reports on a Power BI site
Updating data between Power BI Desktop and Power BI Service
Using Power BI Service tools to modify content online
Sharing reports and dashboards with applications
Integrating Power BI reports into Teams
While both Power BI and Excel are powerful tools, they serve different purposes. Excel is a spreadsheet software primarily used for data analysis and calculations, while Power BI is designed specifically for business intelligence, offering advanced data visualization, analytics, and reporting capabilities.