Data Analysis & Visualization with Power BI

5/5 - (2 votes)

Data Analysis & Visualization with Power BI

What is Power BI?

Power BI is a suite of business analytics tools, which includes both desktop (Power BI Desktop) and web-based (Power BI Service) applications, which:

Deliver insights throughout your organization
Connect to hundreds of data sources
Simplify data prep and drive ad hoc analysis
Produce beautiful reports, then publish them on the web and across mobile devices
Scale across the enterprise, with security and governance built-in

Power BI is the industry leader among BI platforms.

Note: For more detailed information, please visit powerbi.microsoft.com.

Power BI Training Road Map

Part 1: Power BI Desktop
Part 2: Power BI Service
Part 3: Advanced Dax
Part 4: PL-3000 Exam Prep

Part 1 Power BI Desktop

What You Learn in This Course

By the end of this 2-day Data Analysis with Power BI course, participants will be able to use Power BI Desktop to:

Prepare Data:

Use Power Query editor to connect to source data; clean, shape, and transform tables; edit, merge and append queries; load data, etc.

Model Data:

Build relational data models, create table relationships, understand cardinality, explore filter flow, etc.
Use DAX functions, add calculated columns and measures, write DAX formulas for business metrics, etc.

Visualize Data:

Use various types of charts and visuals, customize formats, edit interactions, apply filters, slicers, drill-through, bookmarks, etc.

Analyse Data:

Use Power BI analytical capabilities, including AI visuals, i.e. Q & A, smart narrative, key influencer, forecast, decomposition tree, anomaly detection, etc., to analyse data and gain actionable insights.

Workshop Leader

Michael Shane

Data analysts can extract invaluable business insights and information from business transactional data with Business Intelligence by analyzing monthly behaviors, trends, and outliers, if any, of sales volumes, prices, and costs, etc., in their smallest granularity for the past several years. Top management can leverage them – when modeling their Strategic Plan and Annual Budget – to challenge, adjust, defend and justify business strategy and reasonableness of projection assumptions used in the financial model to make more informed and data-driven business decisions.

Michael is a passionate and robust proponent of Synergy of Business Intelligence and Financial Modeling. To promote this synergy using Microsoft Power BI and Microsoft Excel, he currently provides such synergy services and Power BI training to finance professionals in corporations. He hopes that businesses in Indonesia will commonly practice such synergy as it helps top management to make better business decisions that will lead to better profitability and healthier cash flows.

In his previous employment with Deloitte Indonesia, he assisted the firm’s top management in developing and implementing the firm’s internal self-service business intelligence and analytics using Microsoft Power BI for generating business insights which are indispensable for more accurate planning, budgeting, and forecasting as well as for aligning and fine-tuning business strategies and making more informed and data-driven business decisions.

He developed and regularly maintained Business Intelligence reports and dashboards using Microsoft Power BI for Deloitte’s Clients & Industry team.

As part of Deloitte’s Audit Analytics team, he also performed audit analytics using Qlik Sense to support Deloitte Audit teams.

In the earlier part of his employment, he assisted in a cloud-based accounting application project organized and led by Deloitte Audit Advisory Services team.

Training Experience

He was also part of Deloitte Indonesia’s training team and assisted in delivering the following monthly training:

Firm-wide internal Training and Public Training on Business Intelligence using Microsoft Power BI, Covering Data Transformation, Data Modeling, Data Analysis with DAX, and Data Visualization.
Public training on Financial Modelling using Microsoft Excel, covering Financial Modeling Standards, Financial Modeling Fundamentals, Financial Modeling for Planning & Budgeting, and Sensitivity & Scenario Analysis.

Michael holds a master’s degree in information systems management from BINUS University and is a Microsoft Certified Power BI Data Analyst.

Schedule 2026

19-20 January 2026
12-13 February 2026
12-13 March 2026
13-14 April 2026
18-19 May 2026
11-12 June 2026
13-14 July 2026
13-14 August 2026
10-11 September 2026
15-16 October 2026
12-13 November 2026
10-11 December 2026

Full Day Training, 09.00-17.00 wib

Venue

Swiss-Belinn Simatupang, Jakarta Selatan
Swiss-Belhotel Pondok Indah, Jakarta Selatan
Ibis Styles Simatupang, Cilandak, Jakarta Selatan

Outline Training

Introduction to Power BI Desktop
- What is Power BI?
- Why Power BI?
- Power BI vs Modern Excel
- Power BI Interface
- Power BI Workflow
- Report View Tabs
- Report View Tabs (Contextual)
- Data View & Model View Tabs
- Helpful Resources
Data Preparation
- Types of Data Connectors
- Query Editor
- Query Editing Tools
- Basic Table Transformations
- Text-Specific Tools
- Number-Specific Tools
- Date-Specific Tools
- Creating A Basic Calendar Table
- Adding Index Columns
- Adding Conditional Columns
- Grouping & Aggregating Data
- Grouping & Aggregating Data (Advanced)
- Pivoting & Unpivoting
- Merging Queries
- Appending Queries
- Data Source Settings
- Modifying Queries
- Refreshing Queries
- Defining Data Categories
- Defining Hierarchies
- Importing Models from Excel
- Best Practices
Data Modeling
- What Is a Data Model?
- Database Normalization
- Data Tables vs Lookup Tables
- Primary Key vs Foreign Key
- Relationships vs Merged Tables
- Creating Table Relationships
- Creating “Snowflake” Schemas
- Star Schemas vs Collie Layout
- Managing & Editing Relationships
- Active vs Inactive Relationships
- Relationship Cardinality
- Many-to-Many Relationship
- One-to-One Relationship
- Connecting Multiple Data Tables
- Filter Flow
- Two-Way Filters
- Two-Way Filters: A Word of Caution
- Hiding Fields from Report View
- Best Practices
Data Analysis Expressions (DAX)
- What Is DAX?
- Calculated Columns
- Measures
- Calculated Columns vs Measures
- Adding Columns & Measures
- Quick Measures
- Implicit vs Explicit Measures
- Understanding Filter Context
- Step-by-Step Measure Calculation
- DAX Syntax
- DAX Operators
- Common Function Categories
- Basic Date & Time Functions
- Basic Logical Functions
- Text Functions
- RELATED
- Basic Math & Statistical Functions
- COUNT, COUNTA
- DISTINCTCOUNT
- COUNTROWS
- CALCULATE
- ALL
- REMOVEFILTERS
- FILTER
- Iterator (“X”) Functions
- Time Intelligence Formulas
- Best Practices
Data Visualization
- Power BI Report View
- Inserting Objects, Charts, Visuals
- Formatting Options
- Filtering Options
- Editing Report Interactions
- Drill-through Filters
- Adding & Linking Bookmarks
- What-If Parameters
- Managing & Viewing as Roles
- Importing Custom Visuals
- Desktop & Phone Layout
- Publishing to Power BI Service
- Best Practices
Artificial Intelligence with Power BI
- Analyze Your data using the dashboard You created
Q&A