ETL
What is the role of ETL in data analytics?
Answer:
ETL is key to data analytics. It ensures data is clean, organised, and ready to use. This enables businesses to report, visualise, and make decisions based on accurate analytics results.
Related ETL Questions And Answers
- What are the main steps of the ETL process?
- What programming languages are used for ETL?
- What is the difference between ETL and ELT?
- Will AI replace ETL developers?
- What is ETL used for?
- ETL vs ELT: which approach fits modern cloud data stacks better?
- ETL vs Reverse ETL: which one drives more business impact?
- Batch ETL vs Streaming ETL: which is better for near-real-time analytics?
- What is the difference between ETL and data integration?
- Is it better to use ETL or Apache Spark for large datasets?
- Is ETL used for real-time data processing?
- What are the best practices for optimizing ETL performance?
- Is ETL better than data warehousing?
- What are the disadvantages of using ETL?
- What are the most popular ETL tools?
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