Data Lakehouse
Data Lakehouse While data lakes are known for their flexibility and cost efficiency, a data warehouse scores points with its robust data management function.
A data lakehouse is a novel, open data management architecture that combines the benefits of a data lake with those of a data warehouse. It has the flexibility, cost efficiency and scalability of a data lake combined with the data management functionalities of a data warehouse.
In the data lakehouse, data is stored in its native format (raw data) and then enriched with the help of structured metadata. In contrast to a data lake, relevant data sets are processed structurally — just like in a data warehouse. In this way, business intelligence (BI), reporting, analytics and machine learning (ML) can then be enabled on a single platform.
Data Lakehouse benefits
The key advantage of a data lakehouse is that both structured and unstructured data can be stored, searched, processed, and linked.
Using data lakehouse in the company
A data lakehouse unifies the concepts of a data warehouse and a data lake. It enables effective data availability and an efficient data infrastructure for companies. In addition to costs, this also significantly reduces workload, as there is no need to manage multiple separate systems for storage, integration, or analysis. However, it should be noted that building a lakehouse from the ground up is complex and in most cases a ready-made data lakehouse solution is used.
