Data Analysis with Power BI involves using Microsoft Power BI, a powerful business intelligence tool, to transform raw data into meaningful insights through interactive reports and dashboards. Power BI helps users visualize data, create reports, and share insights across an organization, facilitating data-driven decision-making.
Overview of Power BI: Introduction
to Power BI Desktop and Power BI
Service
Understanding Power BI
components: Dataset, Report,
Dashboard
Connecting to data sources: Excel,
CSV, databases (SQL Server,
MySQL, PostgreSQL), web sources
Data loading and transformation
using Power Query Editor
Query Editor functionalities: Data
cleaning, shaping, merging,
appending queries
Introduction to DAX (Data Analysis
Expressions) language for data
modeling
Creating basic visualizations: Bar
charts, line charts, pie charts
Formatting and customizing visuals:
Colors, axes, legends
Using filters and slicers for interactive
visualizations
Geographic and map visualizations:
Using Bing Maps, ArcGIS Maps
Hierarchical data visualization:
Treemaps, sunburst charts
Custom visuals and importing from
the Power BI AppSource
DAX Functions:
Aggregations: SUM,
AVERAGE, MIN, MAX
Time intelligence functions:
TOTALYTD,
SAMEPERIODLASTYEAR
Calculated columns and
measures
Creating calculated tables and
hierarchies for advanced analytics
Implementing statistical functions in
Power BI
Forecasting trends using built-in
forecasting tools
Applying machine learning
algorithms via Azure Machine
Learning integration
Publishing and sharing reports and
dashboards on Power BI Service
Creating and managing workspaces:
App workspaces, personal
workspaces
