Introduction

• Self-Service BI

• Tool structure and architecture

• Development workflow with Power BI (understanding      the end-to-end flow)

Data Import and Transformation Using Power BI Query Editor

• Introduction to Power BI Query Editor

• Extract – Importing data from various sources:

  • Files (Excel, text)

  • SQL databases

  • Folders

• Transform – Data transformation and process automation

• Creating a date dimension (enabling slicing and analysis by day of week, month, quarter, and year)

• Developing automated data transformation processes:

  • Joining tables

  • Creating calculated columns

  • Data filtering

  • Splitting and merging columns

  • Data cleansing

Introduction to the M language

Modelling and Measure Creation for Interactive Data Analysis

• Data modelling best practices

• Methodologies for developing data models

• Introduction to Star Schema and Snowflake Schema

• Defining and managing relationships between      tables

Measures

• Overview and definition of measures and KPIs

• Introduction to the DAX language and the impact of the data model on measure design

• Developing measures using DAX

• Creating time-intelligence measures for period-over-period comparison and cumulative calculations

Reports

• Report design and development

• Best practices and tips for effective report design

• Using filters and various visualizations

• Adding custom visuals and colour themes from Microsoft AppSource

• Using bookmarks, tooltips, and drill-through functionality

• Using buttons for enhanced interactivity

• Mobile-optimized report design

Power BI Service – The Power BI Cloud Environment

• Introduction to the Power BI cloud service

• Publishing the model from Power BI Desktop to the cloud workspace

• Installing and configuring the Gateway

• Creating dashboards

• Sharing reports and dashboards

• Managing user permissions and workspaces

• Scheduling automatic data refresh and configuring data sources via the Gateway