Explain UNION ALL, in SQL to an Interviewer when attending Data Scientist interview _ Episode 38

Explain UNION ALL, in SQL to an Interviewer when your attending Data Scientist interview _ Episode 38
In data analysis, combining datasets from different sources or time periods is common. As a Data Scientist, you often work with partitioned tables, historical logs, or segmented data. Here, UNION ALL becomes important because it allows merging multiple result sets without losing any records. Unlike UNION, which removes duplicates, UNION ALL preserves them—this is crucial when duplicates carry analytical meaning, such as repeated transactions, multiple logins by the same user, or recurring purchases.

Importance of UNION ALL:

1 Preserves duplicates – In analytics, duplicates often reflect real-world behavior. Removing them may lead to incorrect insights, like undercounting sales or logins.

2 Performance advantage – Since UNION ALL does not perform duplicate elimination, it is faster and more efficient for large datasets, which is essential in big data analysis.

3 Data consolidation – Perfect for combining datasets across time periods, regions, or sources where all entries must be included for accurate statistical modeling.

4 Transparency in results – Helps analysts see the data “as it is” without automatic filtering.