Participants will acquire the necessary skills to clean and restructure data, which will lead to improved data analytics and more reliable insights.
Course ID: CRDPQ
Cleaning and Restructuring Data With Power Query
Learning Objectives
Upon completing this course, you will be able to:
- Extract data from various types of data sources.
- Detect incorrect, inconsistent, incomplete, and invalid (dirty) data.
- Correct dirty data and enhance the reliability of your analytics
- Detect ill-structured data.
- Correct ill-structured data and improve the effectiveness of your analytics.
- Integrate data through model building.
Major Topics
An essential part of data analytics projects is the cleaning and restructuring of data. In this workshop, attendees will gain hands-on experience with Power Query, Power BI’s data preparation tool. Through a case study, participants will address over twenty common data challenges, learning to detect and correct them using Power Query. The workshop encompasses a variety of data preparation techniques, including data extraction and loading, column and table renaming, column splitting and merging, detecting and correcting dirty data, defining data types, creating primary keys, unpivoting columns, combining tables, and creating dimensional models.
Who Should Attend
Anyone who needs to clean and restructure data. Data preparation is essential for all businesspeople who analyze data, but especially for auditors and other finance and accounting professionals.
Fields of Study
Information TechnologyPrerequisites
None