Oracle DaaS vs. Informatica Cloud Data Quality

Best scenario is digital advertising campaigns where there is a specific data need like purchase based targeting or account based marketing and there is room to generate new consumers. Worst scenario when you have a very specific set of consumers or objective to reach that would benefit from the additional users reached within the modeled portion of the data.

Incentivized

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

• Customer Service
• Transparency
• Connect ability

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

• Prices and plans are higher not for mid level companies.
• Not supported to all programming languages.
• Need to go with more detail in user interface.
• Provide more support to customers.

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.

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

Oracle is fast enough to use also we can Match Data About Matching and Enriching Record sMatch Data in Oracle Sales Match Data in Eloqua Match Data in Other Oracle Cloud Applications Export Account Hierarchies, Manage Mappings Typical Workflow for Using Mappings Explore the Mappings Page Create Mappings Create New Mappings Create Mappings for Oracle Sales Create Mappings for Eloqua Create Mappings for Other Oracle Cloud Applications Edit Mappings Edit Existing Mappings Edit Sales Mappings Edit Marketing Cloud Mappings. these are my favourite topics that I use in Daas

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

• Costs are increase but production is also increase.
• Need more UI features.
• Better DB integration provide more support to the code.

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