A cloud data lake is a centralized cloud-hosted repository designed to store an organization’s structured, semi-structured, and unstructured data at any scale. It supports data regardless of its format or source and has no inherent size limits. Using a cloud data lake, an organization can minimize capital expenses for hardware and software, accelerate the deployment of analytic solutions on the market, and collect all data on a single platform with robust governance, security, and control. A cloud data lake also enables the concurrent execution of workloads, including data loading, analytics, reporting, or data science.
How does it work?
Data takes four steps interacting with a cloud data lake: ingestion, storage, processing, and analytics. Initially, data undergoes ingestion where it is assembled and transferred into a cloud data lake without changing its format. Ingested data is kept in storage before any transformations take place.
The next step, processing, is about converting raw data into a compatible format, allowing for further analysis. Lastly, processed data is subject to self-service analytics performed by data scientists and other specialists.
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