Informatica Cloud Data Quality vs. Parrot Analytics

We used Informatica Data Quality to measure the "Data Quality Score" of internal and external reports at my company. Business users set up data profiling and prepared detailed analysis documents for business analysts. and developers developed Data Quality Mapplets for other IT teams to import their Informatica Power Center repositories. Results are stored in a centralized data quality space and then reported and summarized to related business users in detailed ways. At the end of each project, we are now able to place a "Data Quality Score" watermark score on each report involved.

Incentivized

It is well suited for products where there are a lot of users at scale performing and interacting with the platform. Also where businesses need to take informed decisions based on mass users performing actions at scale. Therefore demand analytics tools like Parrot can be a real boon for such businesses. It is less appropriate for those who are not having users at that scale. Scale is very important I believe and analytics can be even more powerful once we have a lot of data on our hands.

Incentivized

• Watch the data real time- After creating the job the data quality engine checks and run the custom rules creating a navigation window at the bottom for review and accessing the data right away.
• Character Set Mapping
• 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

• In-depth Demand Analytics of core features.
• Proper recommendations of features.
• Popularity tracking of the core data that we have and mapping with users.

Incentivized

• Several partnerships diminishing the value of technologies
• Unable to get list of objects from Repository (like sources & targets) that don't have any dependency
• Scheduling: The built-in scheduling tool has many constraints such as handling Unix/VB scripts etc. Most enterprises use third party tools for this.

• Audience behaviour dataset can be improved.
• Demand tracking for features can have more metrics to get even more granular.

Incentivized

I gave a rating of 8 due to the fact that we use Informatica for both our data quality product and ETL product. Having both integrated makes it so much easier. Microsoft had a similar product of finding duplicates, but at the time it didn't seem mature enough. The usability also in IDQ was pretty easy to navigate and use.

Easy to use not only for developers but also business users

Incentivized

The application works well except an occasional error out while using the system. It usually gets fixed when restarting the Infa server

Incentivized

Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.

Incentivized

Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of working closely with several programs. Finally, Informatica Data Quality design is authentic and allows personalization.

Incentivized

Scalability works as expected and it is truly an enterprise system.

Incentivized

• Integration with tools like PowerCenter helped faster delivery of product, and at the same time conversion
• Reduce overall project cost due to bad data , bad quality, exceptions identified nearing go-live and post production
• Employee efficiency is increased exponentially due to more automated, customized tool

• We were able to capture data metrics by almost 25% more as compared to another analytics tool we previously used.
• Recommendations of new data grew by at least 15%.

Incentivized