Data Lakehouse Platform Fundamentals Quiz

Questions and Answers

False

To provide a layer of compute, data warehousing management, and AI/Analytics over cloud storage

False

True Signup and view all the answers

Keeping data warehouses in sync with the system of record in the data lakes Signup and view all the answers

False Signup and view all the answers

Data warehouses are used for Business Intelligence workloads while data lakes are used to store vast amounts of data Signup and view all the answers

True Signup and view all the answers

False Signup and view all the answers

Study Notes

Cloud storage is ubiquitous and the standards and protocols for its use are well-defined.
Adding a compute, data warehousing management layer, and AI/Analytics over cloud storage is what Databricks does with their data lakehouse platform.
The volume of data that emerged in the last decade forced technologies and enterprises to develop newer strategies. This is how the lakehouse took shape.
A gap exists between a data lake and a data warehouse in how they are addressed from a technology and platform perspective.
Data warehouses are used for structured data to drive Business Intelligence workloads. Then you have vast amounts of data that an organization collects daily and is stored in the data lakes.
When somebody wants to take data and do Business Intelligence, they copy a subset of that data, create a new data warehouse, and run those reports.
But what happens is sometimes the data warehouse gets updated and runs out of sync with the system of record in the data lakes. So this is one of the challenges that create a drift in data within an organization that data lakehouse tries to address.