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This two-day course combines the robust data processing capabilities of Microsoft Power Query with the efficiency of AI tools to empower participants in performing advanced data cleansing and transformation tasks. Through practical exercises and real-world applications, participants will learn how to automate data workflows, handle complex transformations, and use AI-enhanced features to streamline data management. By the end of the course, attendees will be well-equipped to handle diverse data scenarios with confidence and efficiency.

What will you learn in this Microsoft Power Query with AI Tools: Data Cleansing and Processing

– Confidently navigate Microsoft Power Query, understanding its interface and purpose in data processing.
– Import and manage data from various sources, leveraging parameters for dynamic connections.
– Perform basic and advanced data cleansing techniques, including filtering, sorting, and heandling duplicates.
– Apply AI tools for intelligent data insights, error detection, and automation of repetitive tasks.
– Execute complex transformations, such as pivoting, unpivoting, and aggregating data.
– Optimize data workflows with error handling, query optimization, and best practices.
– Utilize Power Query M language for creating custom functions and automating processes.

Course Outline

Module 1: Introduction to Microsoft Power Query and AI Tools

– Overview of Microsoft Power Query and its role in data transformation.
– Introduction to AI tools for data automation and intelligent insights.
– Exploring the Power Query Editor interface.

Module 2: Connecting to Data Sources

– Importing data from various platforms (Excel, CSV, databases, web, etc.).
– Using parameters for dynamic and flexible connections.
– Understanding query folding for efficient data processing.

Module 3: Basic Data Transformations

– Filtering and sorting data for better organization.
– Handling duplicates, null values, and data type conversions.
– Introduction to AI-powered error detection and correction.

Module 4: Advanced Data Transformations

– Text and date transformations for precise data adjustments.
– Creating custom and conditional columns using Power Query expressions.
– Utilizing AI tools to predict data patterns and generate insights.

Module 5: Combining Queries and Managing Relationships

– Understanding query dependencies and join types.
– Merging and appending queries effectively.
– Managing relationships between queries for integrated workflows.

Module 6: Error Handling and Query Optimization

– Identifying and resolving errors in Power Query.
– Optimizing query performance for large datasets.
– Best practices for building reliable and efficient data workflows.

Module 7: Automating Progresses with Power Query and AI Tools

– Introduction to Power Query M language for custom functions.
– Automating repetitive tasks using AI-enhanced tools.
– Integrating Power Query processes seamlessly into Excel workflows.