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Oh boy, am I asked again to compare two SQL based reports?

14 January, 2016 10:58:56 AM · Martin

Do you know what’s difficult and prone to errors? Interpreting a complex SQL query that someone else wrote a year ago. Do you know what makes this scenario even worse? Having two different versions of such a SQL query, and it being up to you to figure out the difference.

At SQLdep we pride ourselves on greatly cutting time spent on SQL impact analysis. Our brand new feature fits perfectly the scenario I just described. Submit two versions of the same SQL query or a stored procedure and you can visually track the differences in the data lineage.

Yeah, that is not just comparing the diff as a text. With us you can see within seconds whether the table structure has changed, whether the same columns are used in both queries. Or even whether one column is all of a sudden used multiple times in the newever version of the SQL query.



Do we have your attention now? Cool, because all this is applicable not just to a pair of SQL queries but to a whole batch of queries as well. For example if you have a financial report consisting of a sequence of SQL queries you can submit how the report was calculated today versus 2 months ago. We will show you the visual difference in seconds.

This is essential whenever you have to comply with regulatory requirements and be able to answer how the data was computed at two different points in time. Yearly financial reports are a good example as the methodology might have changed, leaving you needing to understand what exactly what’s happened without spending days digging through old code.



A visual SQL query comparison is available also through REST API. You just submit two versions of the same SQL query and within seconds the visualisation is ready. A must have feature for custom ETL tools or reporting systems allowing users to write custom SQL queries.

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SQLdep saved GE Money twelve months of work. GE Money was searching for ways to make the development and administration of its 20TB data warehouse faster and more efficient.