A data lakehouse is a combination of a data lake and a traditional data warehouse, combining the benefits of both principles & underlying technologies.
A data lakehouse is used to store and process raw data, as in a data lake. However, it is also possible to structure and organize the data in a way suitable for analytics, such as in a data warehouse. In addition, the managing the data becomes easier since things like data lineage are supported.
A data lakehouse can be used by data analysts as well as data scientists to access the data they need. The fact that this can be both structured tabular data and unstructured data makes the solution unique and brings the data science & data analytics worlds closer together. Another advantage is that data users can choose which query or scripting language they use to access or write away the data.
A data lakehouse provides the ability to respond quickly to changing needs and combine data from different sources, while at the same time maintaining the structure and organization of the data to make it easier to analyze.
An interesting article (in English) with more details about a data lakehouse is here to be found.
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