Becoming a data driven organization, supporting data science initiatives, or running an array of data driven applications need a coherent data platform approach to be successful. If ignored or done wrongly, data driven programs fail, falter or lag unnecessarily in the transition from working data science code to a production system that delivers reliable business value. Slow development speed, bad data quality, high maintenance toil, compliance-as-afterthought, security vulnerabilities, scaling pains and service downtime; preventable problems that can turn a good idea into an expensive failure.

We have compressed years of experience in successfully designing, building and operating large data intensive systems at a large variety of organizations into a structured approach to data architecture.

This structured approach to data architecture puts the delivery of business value first and allows you to make clear choices in design trade-offs before they become a problem.

Our course “Introduction to Data Architecture” teaches you that structured approach. You will learn:

• The basic building blocks of data architectures

• Common data architecture patterns and their trade-offs

• The 7 core principles of Data Architecture and how to apply them

• How to guard value and increase iteration speed using the process and deliverables of the Data Architecture Journey

• How to formulate a high-level implementation plan based on business needs

• How to identify and analyze the gap between the business needs and the existing data landscape

• To apply this approach in workshops based on real-world cases