Informatica Cloud Data Quality

It has great function that will aid using hybrid cloud for data storage possible. Customer support is very well. Data virtualization has made us achieved three major things one reduced expense, reduced risk as well as an improved revenue in total and we have a single access point to monitor the data

• It makes it possible to integrate data from multiple disparage sources
• It is great tool to leverage if you want to create data virtualization layer for apps

• Scalable flexible solutions driving data management in financial services
• pretty good integration tool but need to consider third party integrations

Informatica Data Quality is a solution that pushes companies to take a vibrant step in managing data, enhancing and reinforcing security, and activating all the analytical demands in the business. Further, Informatica Data Quality focuses on data collaboration and standardization, a form that improves the quality and reliability of the database system. Finally, the whole validation and cleansing process is effectively supported by Informatica Data Quality, from address verification to content filtering.

• Efficient collaborative application, with the standardization procedures.
• Further, suitable and appropriate cleansing solution, for maximum satisfaction.
• More so, Informatica Data Quality generates proper analytical reports, which are authentic and fundamental in streamlining decisions.

• Enhanced master data management allows complex details to be easily analyzed without the system getting to breakdown.
• Further, Informatica Data Quality has proper validation, cleansing, and safety measures, that keep our database secure and accurate.
• Finally, Informatica Data Quality facilitates predictive analytics, very affirmative for demand budgeting.

Oracle Autonomous Database and SAP Data Quality Management

Column Information Security, CloudApper Safety, BarCloud Stock

IDQ is used for data cleansing and address validation. Passing Invalid Addresses and getting output as valid address and using these address to send mail to employees. Data cleansing rules while loading data from source to warehouse.

• Address Doctor
• Cleansing transformations like labeller .
• Deduplication using match transformation
• Thin client version

• ROI will be good when the product has used over a long period.

Informatica MDM

• We already had the licenses of the product with the Informatica Data Integration family.
• Installation steps could be simplified.
• It would be better if the product had fewer hardware needs.

Oracle Enterprise Data Quality and SAS DataFlux

Oracle Enterprise Data Quality, SAS DataFlux

Automation of technical and business data quality checks on data from over 10 different data sources across various sectors. Access to end-users on the data profiles makes the company proactive in resolving data quality issues which in turn improves the trust in data. Eventually promotes business decisions backed by data.

• Metadata / business glossary
• Data quality automation
• Data profiling

• Overall DQ efficiency
• Easier to understand data before writing the ETL code for the developers
• Increased business user participation

Microsoft Azure