The data lake architecture is a store-everything approach to big data. Data are not classified when they are stored in the repository, as the value of the data is not clear at the outset. As a result, data preparation is eliminated. A data lake is thus less structured compared to a conventional data warehouse. When the data are accessed, only then are they classified, organized or analyzed.
Hadoop, an open-source framework for processing and analyzing big data, can be used to sift through the data in the repository.
Guide to Data Warehousing
- Implementing a data warehouse is a strong step toward managing data on an enterprise level. This guide covers the factors one should consider when selecting and implementing a data warehousing solution.
Data Warehousing Product Selection Tool
- Compare the Best Data Warehousing Tools
Implementing a data warehouse is a strong step toward managing data on an enterprise level, either for management purposes or business intelligence efforts.