Data Lakes allow organizations to store data as-is, structured, semi-structured, or unstructured, in a secure, encrypted repository without transformation or compromising of the organization’s raw data. Even devoid of structure, hierarchy, or organization of the individual pieces of data; at no time is the data processed or analyzed during the data upload or subsequent storage.
In addition to maintaining the integrity of raw data, Data Lakes also:
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Support big data needs by accepting and retaining all data from all data sources
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Leverage the power of big data and analytics by supporting all data types
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Preserve data potential by storing data in the database without pre-defined schemas, making data highly scalable and versatile
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Increase data versatility by only applying schemas to data on-demand or as needed when an organization is preparing to use the data
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Unify enterprise data into a single database repository, including raw copies of source system data, and transformed data used for tasks such as reporting, visualization, advanced analytics, and machine learning