Hey everyone👋
Check out this article highlighting the differences between Data Mart vs. Data Lake
Here are some major differences from the article:
| Aspect | Data Marts | Data Lakes |
|---|---|---|
| Data Structure and Complexity | Structured and well-defined data tailored to specific business areas. | Diverse and unstructured data types. |
| Data Variety and Exploration | Limited data sources with a focus on a particular business area. | Exploration of various data sources and analysis techniques without upfront schema design. |
| Scalability and Future Growth | Limited scalability; best suited for specific functions. | Scalable and adaptable for significant data growth and incorporation of new data sources. |
| Data Governance and Security | Better control and governance over data quality and consistency. | Requires additional governance measures for data privacy, access controls, and regulatory compliance. |
| Analytics Maturity and Expertise | Suitable for business users and analysts who require a simplified, business-focused view of data. | Requires advanced analytics capabilities and expertise to extract insights from raw data effectively. |
| Data Structure and Schema | Predefined schema based on the specific business area. | Schema-on-read approach, allowing flexibility and agility in handling diverse data types and evolving data requirements. |
| Data Transformation and Integration | Structured ETL process involving data extraction, transformation, and loading into a dimensional model. | Focuses on data ingestion rather than upfront transformation, making it easier to incorporate new data sources without extensive data transformation efforts. Transformation and integration occur at the time of data analysis or exploration within the data lake. |
To learn more about these differences, checkout the full article here⤵️