We live in the era of data. As a data engineer, you are expected to gather data from any number of sources and store it where it can be reliably, consistently, and easily accessed by a wide variety of end users. Database design is too important of a discipline to be anything other than deliberate. In this course, Database Design for Data Engineers, you’ll gain the ability to objectively assess the data you have as well as the requirements and outcomes needed, and properly develop your database design approach to run efficiently, reliably, and securely. First, you’ll explore relational data and ACID concepts, the key benefits and properties that define each relational approach, and the limitations and restrictions of each design approach. Next, you’ll discover the variety of non-relational approaches to data storage, how new capabilities blur the lines that used to define what a non-relational database could do, tradeoffs of the CAP theorem, and other important concepts for making design decisions such as schema flexibility and scalability. Finally, you’ll learn how to implement your design with confidence, and gain further confidence in securing your databases while addressing data integrity, data consistency, and the overall quality of your database. When you’re finished with this course, you will have the skills and knowledge of essential database design concepts to confidently assess your data and make design decisions that will scale, perform, and reliably meet the needs of your organization.
Author Name: Russ Thomas
Author Description:
Currently an IT leader in Denver Colorado’s FinTech sector Russ has focused on database engineering, modelling, administration, and BI since 1997. Russ is a passionate trainer and community volunteer presenting regularly at tech events and local user groups around the US. In 2019 much of Russ’ focus turned to cloud based data lakes specifically on Google BigQuery, and the emerging world of large language models.