The ability to capture and analyze practically any type of data has emerged as a critical business capability. Data lakes are broadly accepting of new data regardless of the format. This is a marked departure from the rule-laden, highly structured storage within traditional relational databases.
With all the media hype around data lakes and big data, it can be difficult to understand how — and even if — a data lake solution makes sense for your analytics needs. In reality, data lakes and data warehouses can complement each other.
In this eBook, you'll learn how a modern data architecture can allow you to continue to leverage your existing investments, begin collecting data you have been ignoring or discarding, and ultimately enable analysts to obtain insights faster.
Business needs that are driving data architectures to evolve & adapt
Principles of a modern data architecture
How data lakes and data warehouses are complementary solutions
Tips for designing a data lake
Azure technologies for implementing a data lake
Considerations for a successful data lake in the cloud
How to get started with a data lake