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Data Activation and Reduction of “Time-To-Insight” Thanks to the Implementation of a Data Mart
The total amount of data created, captured, copied, and consumed worldwide is expected to increase rapidly and exceed 180 zettabytes by 2025. All companies are now faced with arapid increase in data volumes. As a result, many are now using data lakes, usually in addition to their existing data warehouses, to meet their data storage and management needs.
Unlike data warehouses, which allow the storage of structured and transformed data following the ETL process (Extract, Transform, Load), the data lake generally contains structured, semi-structured, or unstructured data that is stored in its raw form. The data lake follows the ELT process (Extract, Load, Transform). Data are extracted from their sources, stored in the data lake, and transformed only when necessary.
The complexity of operating data lakes
The ELT process that applies to data lakes involves ad hoc transformations of data to make it more accessible to business teams. Depending on the frequency of requests, the type of need (alerts, dashboards, ad hoc analyses), and regulatory…
