Every system changes over time, and so do the source systems providing data to warehouses. Let’s see how we can help.
One day an analyst gets a change request to analyze. The sales department has come up with a new line of products that have super-cool names that unfortunately do not fall within the current maximum length for product names.
Therefore, the maximum length for product names has to be increased in the corresponding source system, so the data type for this column in the extract for the data warehouse has to be changed too. Moreover, this value is propagated throughout the whole data warehouse to reports; sometimes it is even concatenated with a product category name, and so on. So, our analyst needs to find all tables, views, workflows, and scripts that might be affected by this change to create a plan for implementation.
What should he do? Well,…
- First, he should ask the ETL department, how this extract is transformed, what workflows work with it, and what tables are filled with the cleaned data. Did you know that both a short and a full name are generated from this value and that one of the code identifiers also goes to other tables?
- Fine, so he gets the list of stage tables. Then, he tries to find documentation in the database detailing how these tables are transformed to the core and also which data marts are built on top of the core. We hope that all the documentation is up-to-date!
- And finally reports: is it necessary to change the reports? What about refreshing the models and republishing the reports? He needs to find all the reports that use these data marts. And there are many of them.
This could take a lot of time and effort, not only for the analyst himself, but also for staff in other departments. Manta Flow can reduce time spent on impact analysis by more than 90%. Do you know how much time you spend on manual impact analyses in your BI department? Our customers have already saved millions of dollars with automation.
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