The Data Lakehouse - why, how, what?
- Data Lake
- Data Warehouse
Following the introduction of the Data Lake concept ten years ago, many companies have benefitted from the flexibility and scalability it offers in storing and analyzing data.
Despite these revolutionary advantages, organizations have still found themselves relying on an ecosystem consisting of both a data lake and a warehouse to meet modern-day business use cases – from traditional BI to Advanced Analytics. Not only is this architecture costly to maintain, but the disconnect between the storage and querying layers can also generate operational inefficiencies and lead to multiple versions of the truth.
Enter the Lakehouse concept: a hybrid set-up that combines the data structures and management features of a Data Warehouse with the low cost and flexible storage of a Data Lake. The result is a refined, revolutionary architecture that eases the development of structured reporting, ad-hoc business querying, and advanced analytics use cases, without the need to navigate different systems or engage in the difficult and costly process of keeping data consistent across them.
In this recorded webcast we explore the Lakehouse concept in detail – answering three main questions: what it is, why it’s revolutionary, and how companies like Databricks and leading cloud providers are making, what began as a vision, a reality.
The Lakehouse What, Why, How (26 mins)
Is it for you
- Are you interested in knowing more about what a Lakehouse is and what purpose it serves?
- Could you benefit from more joined-up analysis of your disparate datasets?
- Are you looking to take advantage of the scalability and flexibility offered by cloud data analytics tools?