Data Models & Manipulation
About the course
Before you can start using data for AI and analytics purposes’ you need to set up the right database architecture, transform data in an efficient way, and make sure data quality is fixed. This two-day badge takes you through this process step-by-step, while directly applying the theory to a case; starting with designing a good data model, identifying and solving the data quality issues, and finally applying the right SQL queries in transforming the data. If you are a Data Scientist, dealing with data quality issues and transformations to create an analysis dataset is all in a day’s work. This training is designed to ensure you are building the most efficient databases which enable easy browsing of the data by providing a compact, well-structured overview. This badge is made up of two parts: the four-hour Data Quality pre-work e-learning, and the two-day course.
Why this is for you
In order to effectively carry out any analysis or develop AI models, you need a proper set-up database and analysis table. When making the translation from a business question to arrive at that stage, it is essential to know how to structure and transform data in the correct way. This module is designed specifically to provide you with all the basics you need to build the necessary well-structured analysis table according to best practice standards.
This training is perfect for starting Data Scientists, AI Engineers and Data Engineers who are eager to learn how to design and get hands-on experience with data modeling and creating a relevant analysis dataset. We require you to have prior knowledge of SQL before doing the pre-work and taking part in this course.
What you’ll learn
An integrated view of the entire process and hands-on practice to gain experience in building proper analysis datasets and learning:
- Applying Entity Relationship Diagrams and Entity Relationship Models
- Dimension modeling
- How to identify and solve the most common data quality issues, including steps to perform a data audit
- Applying the data quality cycle
- How to transform data in SQL
Theory and practical use
- Entity Relationship Modeling – Become confident in explaining and designing an ERD and ERM
- Dimensional Modeling – Explain the rules of dimension modeling and its uses, and design a star scheme
- Applying the data quality cycle – To ensure continuous control and improvement of data quality in periodic processes
- Transforming data in SQL – Apply the most important SQL statements for data transformation
All trainings in the GAIn portfolio combine high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.