Enterprise Architecture with Databricks

Summary

Learn to draft an enterprise-level architecture plan that includes Databricks.

Description

A common struggle that organizations face is how to accurately articulate their data needs and translate those into needs into data management systems.

In this course you’ll learn about how business leaders, admins, and architects use Databricks in their architecture . We’ll cover fundamental concepts about key players: Data Engineers, Data Scientists, Platform Administrator; raw data forms: structured and unstructured data, batch and streaming data, to help set the stage for our discussion on how end users help businesses create data assets like machine learning models, reports, and dashboards. Then, we’ll discuss where components of Databricks Azure fit into an organization’s big data ecosystem. Finally, we’ll review real-world business use cases and create enterprise level architecture infrastructure diagrams.

Learning objectives

  • Create a requirements document which profiles the data needs of an organization.

  • Translate business needs related to data analytics into technical requirements used for drawing an architectural diagram.

  • Translate the Databricks Lakehouse Architecture with Delta to a technical requirements document.

  • Design Azure Databricks architectures that includes integration with Azure services, for real-world scenarios.

  • Evaluate, analyze, and validate detailed infrastructure designs.

  • Create infrastructure designs.

Prerequisites

  • Beginning knowledge about characteristics that define big data (3 of the Vs of big data - velocity, volume, variety)

  • Beginning knowledge about how organizations process and manage big data (Relational/SQL vs NoSQL, cloud vs. on-premise, open-source database vs. closed-source database as a service)

  • Beginning knowledge about the roles that data practitioners play on data science teams (can distinguish between database administrators and data scientists, data analysts and machine learning engineers, data engineers and platform administrators)

Proof of completion

  • Upon 80% completion of this course, you will receive a proof of completion. 

 

Duration

6.7 hours

Part of Learning Pathway(s)