The most axial benefit of a data lake is the centralization of disparate data sources. Data can be collated from multiple silos to form a unified source of truth. Big data, search, and analytics techniques can then combine and process these sources which are otherwise not possible.
The flexibility offered by data lakes enables enterprises to apply suitable security measures to protect any proprietary information and set up access levels. Security levels can also provide granular control which grants the user access to any information without the visibility of the source of the data. This can be beneficial under numerous circumstances such as the non-applicability of data source, licensing limits of the original content source, or the presence of obsolete or decommissioned data sources.
The accessibility of data lakes makes normalization and enrichment of the data an easy process. Data preparation practices such as indexing, de-normalization, metadata extraction, aggregation, format conversion, cross-linking, augmentation, or entity extraction are all simplified. This established method of data preparation also helps optimize costs by reducing upfront data preparation charges.
Moreover, the flexibility of access facilitated by data lakes allows organizations to collect data from anywhere around the globe and promote content re-usage to drive critical business decisions. On the whole, data lakes can foster data democracy within an organization and foster agility and innovation throughout.