Microsoft Azure Data FundamentalsDescribe core data conceptsMedium
A data scientist is working with a large dataset of customer feedback, which includes text reviews, star ratings, and product categories. The goal is to identify common themes and sentiment within the text reviews. Which data processing option is most appropriate for this task?
- AOnline Transaction Processing (OLTP)
- BBatch Processing
- CStream Processing
- DOnline Analytical Processing (OLAP)
Show answer & explanationAnswer & explanation
Correct answer: D. Online Analytical Processing (OLAP)
Analyzing customer feedback for themes and sentiment involves complex queries and aggregations over historical data, which is characteristic of OLAP.
Why the other options are wrong
- A. OLTP is for high-volume, real-time transaction processing, not complex analytical queries.
- B. Batch processing is about processing data in large chunks, but OLAP specifically addresses the analytical nature of the task.
- C. Stream processing is for real-time analysis of data in motion, not historical feedback analysis.
Online Analytical Processing (OLAP)
A category of software tools that provide fast, interactive analysis of multi-dimensional data from multiple perspectives.
- Optimized for complex queries and aggregations.
- Used for business intelligence, data mining, and decision support.
- Often involves historical and aggregated data.
Memory trick: OLAP for Deep Insights, Not Just Transactions