Databases · DBC-43

Power BI Desktop for Business Analytics

Power BI Desktop for Business Analytics is a course in business data analysis with Power BI, from connecting sources and preparing data in Power Query to star-schema data modelling, DAX calculations, interactive dashboards and publishing to the Power BI Service. It suits data and business analysts, managers who rely on data, and teams that produce regular reports.

Updated 21 Aug 2026

From 6,210 THB / person 6,900 −10% excl. VAT 7% · group rates available

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PDFDownload the course outline

Duration12 hours · 2 days
FormatOnsite / live online
Next roundOn request
CertificateIncluded

Course overview

Business decisions today depend on both the accuracy and the speed of data. Organizations that can turn massive raw data into business insight faster gain a competitive edge. Microsoft Power BI is a business intelligence and analytics platform consistently ranked a market leader, able to connect to diverse data sources, shape and transform data, build a data model, calculate with the DAX language, and present results as beautiful, interactive reports viewable on any platform - PC, tablet and mobile. This course is designed for those who want to analyze their organization's

existing data for business themselves, starting from the fundamentals of business intelligence and the star schema, connecting to data from files, databases and websites, cleaning and transforming data with Power Query, designing table relationships and building calculations with DAX, choosing the right visualizations for business questions, and publishing reports to the Power BI Service to share with the team, set automatic data refresh and view on mobile devices. Every topic comes with a hands-on workshop using sample business datasets so learners can apply it to their real organizational data immediately.

What you’ll gain

Understand business intelligence, data analytics and how Power BI Desktop works, including the star schema data structure
Connect and import data from diverse sources - files, databases, cloud and websites
Prepare, clean and transform data (ETL) efficiently with Power Query, with a basic understanding of the M language
Design and manage data-model relationships correctly
Build calculations with DAX - calculated columns, measures and calculated tables - including basic time intelligence
Choose the right visualizations for business questions and build interactive dashboards with a mobile layout
Publish reports to the Power BI Service, share with others, set automatic data refresh and configure data alerts
Understand licensing, the Power BI Gateway and how to roll out Power BI in the organization

Who this course is for

Data analysts and business analysts
Chief data officers and directors, plus managers and team leads who use data to make decisions
Sales, marketing, accounting, finance, inventory and HR staff who produce regular reports
People who already use Microsoft Excel for reporting and want to move up to interactive dashboards
Anyone who wants to start a career in data analytics and business intelligence

Prerequisites

Comfortable using Windows and the internet
Basic experience with tabular data, understanding rows, columns and data types, and basic data analysis
Able to use PivotTables and create charts in Microsoft Excel
No programming or database background required

Curriculum

Day 1 Power BI Fundamentals, Data Sources and Data Preparation with Power Query

Section 1: Getting to Know Microsoft Power BI

An overview of Power BI and its place in the Microsoft Power Platform, the role of data analytics and the business intelligence concept
How Power BI works (Connect, Transform, Model, Visualize, Share), the components Power BI Desktop, Service and Mobile, and licensing (Free, Pro, PPU, Premium)
Downloading, installing and configuring Power BI Desktop, the working views (Report, Table, Model View) and the star schema (fact and dimension tables)
Workshop: build your first report with Power BI Desktop from the sample data

Section 2: Data Sources for Power BI Desktop

Understanding data sources and connection modes: Import, DirectQuery and Live Connection
Using Excel, Text/CSV, Folder (auto-combining all files), SQL Server, Azure SQL Database, SSAS, Enter Data, and importing from websites and SaaS services
Case study: examining exchange-rate data from the Bank of Thailand website
Workshop: connect data from multiple sources into a single report file

Section 3: Data Transformation with Power Query

The ETL concept, the Power Query Editor and Applied Steps, viewing data quality (Column Quality, Distribution, Profile) and adjusting data types by locale (Buddhist and Gregorian years)
Shaping data: Remove Row/Column, Remove Duplicate and Unpivot Columns, plus data cleansing: Trim, Clean, casing, and Replace Values/Errors
Splitting and merging columns, combining data with Append and Merge Query (join types), creating custom/conditional columns and Group By
Getting to know the M language and Advanced Editor, using parameters and groups, plus a workshop: turn unready sales data into an analysis-ready table

Day 2 Data Model, DAX, Building Dashboards and Publishing with the Power BI Service

Section 4: Working with the Data Model in Power BI Desktop

The data-model concept, why fact and dimension tables are separated, and managing relationships, cross-filter direction and cardinality
Formatting fields (format, currency, percentage), setting implicit measures (summarization) and data categories for maps, links and images
Building hierarchies for drill-down, setting Sort by Column (e.g. months in calendar order) and hiding unnecessary fields
Workshop: design a star-schema data model from the tables prepared on Day 1

Section 5: Calculations with DAX (Data Analysis Expressions)

Getting started with DAX, how it differs from Excel formulas, syntax, table/column references and the basics of row context and filter context
Creating calculated columns and explicit measures, aggregation functions (SUM, AVERAGE, COUNT, DISTINCTCOUNT), logical functions (IF, SWITCH) and CALCULATE
Relationship functions (RELATED, RELATEDTABLE), building a Date Table and Mark as Date Table, plus basic time intelligence (running totals, prior-year comparison) and calculated tables
Case study: computing product age and age bands, plus a workshop: build a set of measures for business KPIs such as sales, profit, margin and growth

Section 6: Building Dashboards with Power BI Visualizations

Choosing the right visualization for the data: Card, KPI, Table & Matrix (conditional formatting), Bar/Column, Pie/Donut, Treemap, Combo, Map, Scatter and Waterfall charts
Setting filters (Slicer, Visual/Page/Report Filter), Edit Interactions, Drill Down, Drill Through, Tooltip Page, Bookmarks and Buttons
Layout, color themes and readable dashboard design principles, and building a mobile report with Mobile Layout
Case study: a Sales Performance Report shown on a mobile device, plus a workshop: design and build a complete interactive sales dashboard

Section 7: Using the Power BI Service

Publishing reports to the Service, the Workspace, Semantic Model, Report and Dashboard structure, and Publish to Web with security precautions
Building a dashboard with Pin Visual, natural-language queries (Q&A), sharing reports (Share, App, Workspace Role) and exporting to PDF, PowerPoint and Excel
Setting up a subscription to email reports, configuring data alerts, and viewing reports on Power BI Mobile
Getting to know the Power BI Gateway and setting up scheduled refresh, plus a workshop: publish a dashboard, share it with teammates, set a data alert and view it on Power BI Mobile

Schedule & training options

For individuals — public rounds

No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770

Join the waiting list Ask about rounds

For organisations — in-house / private

Tailor the content to your team’s tools and projects
Your dates, at your office or live online
Quotation with tax ID for procurement

Corporate training quote

Instructors

Samit KoyomFounder & CEO, IT Genius Engineering

Frequently asked questions

What is a star schema and why does it matter in Power BI?

A star schema places a central fact table holding transaction figures, such as sales amounts, quantities and dates, surrounded by dimension tables describing products, customers, branches and the calendar, linked one-to-many. This structure lets Power BI filter and summarise quickly, makes DAX formulas simpler and more reliable, and avoids ambiguous relationships.

What is the difference between a calculated column and a measure in DAX?

A calculated column is computed row by row when data is loaded or refreshed and stored in the table, so it uses memory and suits values you group or filter by, such as customer age bands. A measure is calculated at query time according to the filters selected in the report, such as total sales or profit margin, so it takes no storage and responds to context. As a rule, summary figures should be measures.

What are the steps to build a dashboard in Power BI Desktop?

Connect to your data sources, such as Excel, CSV or a database, then clean and shape the data in Power Query. Build star-schema relationships in Model view and write DAX measures for the key figures. Next choose visuals that answer the business questions, add slicers for filtering and lay the page out from overview to detail. Finally publish to the Power BI Service to share the report and schedule automatic refresh.

Who is the Power BI Desktop for Business Analytics course for, and what should I know beforehand?

It suits data and business analysts, managers and team leads who make decisions from data, sales, marketing, accounting, inventory and HR staff producing regular reports, and Excel users who want interactive dashboards. You should understand tabular data and be able to use PivotTables and create charts in Excel. No programming or database knowledge is needed.

What will I be able to do after the Power BI Desktop for Business Analytics course?

You will be able to connect data from files, databases and websites, clean and transform it in Power Query, design a star-schema data model, write DAX measures including basic time intelligence, build interactive dashboards with a mobile layout, and publish reports to the Power BI Service with scheduled refresh and data alerts. Participants who complete the training receive a Certificate of Completion with its own number, which can be verified online.

Can the Power BI Desktop for Business Analytics course be run in-house for our team?

Yes. It can be run in-house for your team, with examples adapted to your own work, such as the sales data or monthly reports your team already produces, and guidance on publishing reports across the organisation. You can request a quotation from this page, or contact us on LINE @itgenius or by phone on 02-570-8449.