The explosion of new data sources has not only provided organizations new opportunities to grow revenues and reduce costs but has also opened the door to possibilities. But manual processes for reconciling fragmented, duplicate, inconsistent, inaccurate, and incomplete data, as well as fragmented point solutions, result in dubious data and delayed business insights that can't be trusted.
A systematic approach that quickly and repeatedly transforms ever-increasing amounts of big data into business value without risk is clearly the ingredient for success. The opportunity to harness data has never been greater—or more achievable—than it is now.
Successful applications of big data analytics technologies have graduated from the realm of proofs of concept or pilot projects. They are now driving competitive advantage with explicit, measureable business goals and outcomes
Data warehouse optimization and data lake initiatives are allowing organizations to lower storage and upgrade costs, on one hand, in order to invest in innovation and exploration, on the other. Organizations are offloading less-used data to Hadoop clusters to decrease storage costs and make more data available to meet business demands.
Manual processes are inefficient and can’t scale inhibit business users from getting the data they need. Organizations need to get more from limited IT resources by providing self-service solutions for business analysts. Organizations are looking to integrate, govern, and secure siloed data in centralized intelligent data lakes to help get the right data to the right people at the right time.
Tinkoff Bank acquires and retains more customers at a lower cost with Informatica Big Data Management.
Western Union built a data platform based on Hadoop and Informatica Big Data Edition
Informatica empowered scientific and clinical collaboration at this renowned cancer center by turning data into knowledge and facilitating self-service business intelligence