IDQ - Simple yet effective
Overall Satisfaction with Informatica Data Quality
We are sourced from heterogeneous relational database's and also from legacy systems like SAP and SAP BW for our data integration project. After addressing multiple bugs and errors on the production data, we learned that Data Profiling and Data Quality was really missed during the analysis stage. We found many data inconsistencies, foreign character problems and issues with simple formats and formulas. Special characters were also one of the many bugs we failed to address in the beginning. Now that we start all the projects with IDQ and only after its help in analysis and fixing the bad guys, it helped us with quite a few production tickets. It also helped us with best end user experience. We are still on top of the learning curve using IDQ, but we are holding up strong with it as is now.
Pros
- Correcting error prone manual data entry across the organization, correcting formulas, rules and methods. Understanding the data properly first to begin with. Improving and approving the accuracy overall.
- Makes sense of our own data, which in turn gives us confidence that we can provide to the end users. IDQ helped us with erroneous data in accounting and HR for accurate and immaculate reports.
- IDQ decreased the capital on Production support and QA time especially.
Cons
- I did not spend any time researching the tool for improvements, but the interface with Power Center will me more interactive and connected to the developers.
- End user experience improved and reporting needs increased with quality.
- Decreasing the overhead on support dollars for less data related errors.
- QA process time decreased.
Data Flux.
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