What Is a Data Lake?
A data lake is a low-cost storage environment, which typically houses petabytes of raw data. Unlike a data warehouse, a data lake can store both structured and unstructured data.
| Also, data lake does not require a defined schema to store data, a characteristic known as “schema-on-read.” This flexibility in storage requirements is particularly useful for data scientists, data engineers, and developers, allowing them to access data for data discovery exercises and machine learning projects. |
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Data Lake vs. Data Warehouse
While both store data, each repository has its own requirements for storage, which makes it an ideal choice for different scenarios.
- For instance, data warehouses require a defined schema (i.e., in a structured data format) to fit specific data analytics requirements for data outputs, such as dashboards, data visualizations, and other BI (business intelligence) tasks.
- Data lakes, on the other hand, incorporate data from both relational and non-relational systems, allowing data scientists to incorporate structured and unstructured data into more data science projects.
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Son: “Father, can you write in the dark?” Father: “Yes, why not?” Son: “Then please turn off the lights and sign my report card.” |