Informatica DataQuality

The world is looking for quality in data. Because great data is good business. Why does quality data matter? “Bad” data costs U.S. businesses $600 billion annually Whether bad data causes you to lose revenue, damages your brand, reduces your competitive edge, or simply results in bad decision-making, the costs are significant How to get the Informatica is comes up with a solution to provide quality data. Have you considered having / working with Informatica Data Quality? Ever wondered how Informatica data quality could be beneficial when powercenter allows you to profile the data? Answer is "Data Quality" does more than profiling.  It is a single, and highly productive environment for profiling, data cleansing and managing data quality rules.

Lets start with some introduction and basic features of it..

Lets see some benefits of Informatica Data Quality -

1. Embedded data stewardship: Our data management platform enables collaboration across your entire infrastructure, not just within specific tools and use cases.
2. “Define once, deploy anywhere”: With Informatica Data Quality, you only need to define your business rules once, and they’ll be applied consistently anywhere—on premises, in the cloud, on Hadoop.
3. Data-as-a-Service excellence: We ensure you can communicate with your customers using accurate contact record verification and superior data enrichment services.
4. One tool that acts as a single platform for data quality; No other tools and extra licenses are required; and that slashes license and maintenance costs
5. Identify, resolve and prevent data quality problems; Data becomes more trusted
6. Effective data profiling and more effective ways to share the profiling rules and results with business; All you need to do is generate a scorecard for the profile and share the URL with business. This enhance trust in business.
7. Enhance IT productivity with powerful business-IT collaboration tools and a common data quality project environment
8. Develop routines like address standardization, exception handling, data masking and integrate them with PowerCenter to utilize them as components / mapplets; I will discuss more about these routines in future posts
9. Universal Connectivity to All Data Sources
10. Centralized Data Quality Rules for All Applications
11. All rules, reference data, and processes can be reused for all types of data integration projects, including data migration, data consolidation, and MDM.