A key component to wrangling data is the data lake framework. In this 9-video Skillsoft Aspire course, discover how to design and implement data lakes in the cloud and on-premises by using standard reference architectures and patterns to help identify the proper data architecture. Learners begin by looking at architectural differences between data lakes and data warehouses, then identifying the features that data lakes provide as part of the enterprise architecture. Learn how to use data lakes to democratize data and look at design principles for data lakes, identifying the design considerations. Explore the architecture of Amazon Web Services (AWS) data lakes and their essential components, then look at implementing data lakes using AWS. You will examine the prominent architectural styles used when implementing data lakes on-premises and on multiple cloud platforms. Next, learners will see the various frameworks that can be used to process data from data lakes. Finally, the concluding exercise compares data lakes and the data warehouse, showing how to specify data lake design patterns, and implement data lakes by using AWS.
Data Lake: Framework & Design Implementation