Course Content
Module 1: Introduction to Excel Power Query
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Video 1: Overview of Power Query: What it is, why use it, and its benefits over traditional Excel methods.
02:00
Video 2: Navigating the Power Query Interface: Understanding the layout, key features, and functionalities.
05:00
Video 3: Connecting to Data Sources: Importing from Excel, CSV, text files, databases, web sources, and folders.
03:00
Video 4: Data Preview and Filtering: Exploring your data, applying basic filters, and understanding filter logic.
10:00
Video 5: Introduction to M Language: Understanding the role of M in Power Query, basic syntax, and using simple functions.
08:00
Video 6: Refreshing and Managing Data Connections: Setting up automatic refreshes, managing multiple connections, and troubleshooting issues.
07:00
Video 7: Getting Help and Resources: Learning about online resources, documentation, and community forums for further learning.
08:00
Module 2: Transforming Datasets for Deeper Insights
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Video 8: Removing Duplicates and Formatting Data: Identifying and removing duplicates, and applying consistent formatting for improved readability.
12:00
Video 9: Text Manipulation: Splitting, trimming, combining, and cleaning text strings based on specific criteria.
10:00
Video 10: Adding and Removing Columns: Creating new columns with formulas or expressions, and removing unwanted columns for streamlined data.
08:00
Video 11: Conditional Formatting and Logic: Applying conditional formatting based on rules, introducing basic IF statements for decision-making within queries.
07:00
Video 12: Date and Time Functions: Working with dates and times effectively using built-in Power Query functions.
09:00
Video 13: Grouping and Summarizing Data: Grouping data by categories and using aggregation functions (SUM, AVERAGE, COUNT) for insights.
09:00
Video 14: Error Handling Basics: Identifying common errors, using Try/Catch blocks for error handling, and cleaning data for better analysis.
12:00
Module 3: Extracting Information from Data
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Video 15: Text Extraction and Combining: Advanced techniques for extracting specific information from text strings using regular expressions or parsing methods.
09:00
Video 16: Web Scraping: Introduction to web scraping basics, ethical considerations, and extracting data from websites.
09:00
Video 17: Combining Data from Different Sources: Merging data from multiple tables based on shared columns, handling missing values, and ensuring data consistency.
07:00
Video 18: Data Cleaning and Validation: Advanced techniques for data cleaning, using custom functions, and validating data integrity.
05:00
Video 19: Data Shaping and Restructuring: Transforming data layout by pivoting, unpivoting, and using custom M functions for complex reshaping.
10:00
Module 4: Combining Multiple Data Sources
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Video 20: Joining and Merging Tables: Understanding different join types (inner, left, right, full), applying filters during joins, and handling large datasets.
08:00
Video 21: Appending and Combining Tables: Stacking tables vertically, de-duplicating data when combining, and maintaining data integrity.
13:00
Video 22: Using Parameters and Customizing Queries: Creating dynamic queries with parameters for flexible data sources and filtering options.
04:00
Video 23: Building Reusable Functions: Creating custom M functions for repetitive tasks, improving workflow efficiency and code reusability.
08:00
Video 24: Error Handling and Troubleshooting Advanced: Identifying and resolving complex errors, using debugging techniques, and optimizing query performance.
09:00
Video 25: Version Control and Collaboration: Sharing and collaborating on Power Query queries, using version control tools for tracking changes.
08:00
Module 5: Troubleshooting and Common Issues
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Video 26: Advanced Error Handling Strategies: Implementing custom error handling routines, using custom messages, and providing user feedback on data issues.
05:00
Video 27: Data Quality Checks and Validation: Building data quality checks within your queries, ensuring data integrity and consistency.
12:00
Video 28: Data Profiling and Analysis: Exploring data characteristics using profiling tools, identifying trends and anomalies.
09:00
Video 29: Performance Optimization Techniques: Optimizing queries for large datasets, using techniques like filtering early and avoiding unnecessary transformations.
09:00
Video 30: Best Practices and Tips: Sharing best practices for building efficient and maintainable Power Query queries, providing tips for continuous learning and improvement.
07:00
Excel Power Query Fundamentals Course in Bangla
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