Excel Power Query for Smart Data Automation
Excel Power Query enables smart data automation by cleaning, transforming, and combining data from multiple sources with minimal effort. It reduces manual work, improves accuracy, and creates repeatable data workflows, helping professionals focus on analysis and decision-making instead of routine data preparation.
Outline
Module 1: Introduction to Power Query
• What is Power Query and why use it?
• Power Query vs Traditional Excel Formulas
• Real-world use cases & business scenarios
• Supported data sources overview
• Power Query workflow (Extract → Transform → Load)
Module 2: Getting Started with Power Query
• Launching Power Query in Excel
• Power Query Interface & Editor Tour
• Queries Pane, Applied Steps & Formula Bar
• Loading data to Excel (Table, Connection Only)
• Refreshing queries & data updates
Module 3: Connecting to Data Sources
• Excel files (Workbook, Tables, Sheets)
• CSV & Text files
• Folder-based data loading (Combine Files)
• Databases (SQL Server overview)
• Web data (Basic introduction)
Module 4: Data Cleaning & Preparation
• Removing & keeping rows
• Removing duplicates
• Handling blank and null values
• Replacing values
• Changing data types correctly
• Splitting & merging columns
• Trim, Clean, Lower, Upper functions
Module 5: Transforming Data
• Sorting & filtering data
• Pivot & Unpivot columns
• Group By (Basic aggregations)
• Conditional columns
• Index columns
• Custom columns
Module 6: Working with Dates & Time
• Extracting Year, Month, Day
• Month Name, Day Name
• Date difference calculations
• Working with Time & Duration
Module 7: Combining Data
• Merge Queries (Joins)
o Left, Right, Inner, Full, Anti Joins
• Append Queries
• Practical merging scenarios
• Handling mismatched data during merge
Module 8: Advanced Power Query Techniques
• Custom Columns using M Language (Basics)
• Understanding Power Query formulas
• Referencing other queries
• Creating reusable queries
• Parameters in Power Query
• Error handling techniques
Module 9: Automating Data Preparation
• Folder automation (Monthly / Daily files)
• Dynamic file paths
• Refresh strategies
• Reducing manual work with Power Query
• Best practices for automation
Module 10: Power Query Performance Optimization
• Query folding explained
• Identifying non-folding steps
• Optimizing transformation order
• Reducing load time & file size
Module 11: Power Query Best Practices
• Naming conventions
• Documentation techniques
• Managing applied steps
• Query dependencies
• Version control tips
Module 12: Power Query for Reporting & BI
• Preparing data for Pivot Tables
• Preparing data for Power BI
• Power Query in Excel vs Power BI
• When to use Power Query vs formulas
Course Fee
● Online
Rs. 5,000/- Total
- Once paid, the fee is non-refundable and non-transferable
Account Details
Bank: Habib Bank Limited
Account Title: AIN GenX
Account No: 5910-70000512-03
IBAN No: PK08 HABB 0059 1070 0005 1203
Faciliators
Irfan Bakaly
Data Analyst
25+ years of experience in Data Analysis
Noor Surani
Tech Entrepreneur
25+ years of experience in Data Analysis
Who this course is for:
Finance professionals, Accountants and auditors, Financial analysts and investment professionals, Managers involved in budgeting, forecasting, and reporting, Students or graduates
Duration
● 4 Weeks (10 Hours)
Classes
● Online via Zoom
Schedule
- Day: Sunday's Only
- Timing: 11:00 - 01:30 pm (PST)
Starting From
● Sunday, 08 February, 2026
Participants from Top Organizations
Certificates
