Big Data Analytics

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Webinar: Faster, More Trusted Big Data Analytics Using Data Lake Management Innovations

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Meeting Big Data Challenges

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.


Achieving Business Value

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 

  • Sales and marketing operations are collecting customer and market data for its potential to improve experiences and drive business growth.
  • Financial institutions are saving and monitoring transactional data and other related signals in order to enrich fraud detection techniques, keep up with changing global regulations, and boost consumer trust in the security of their services.
  • Healthcare organizations are preserving electronic medical record data and claims data in order to drive more personalized healthcare.

Refocusing IT Resources

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.



Analytics expert David Lyle explains how IT can align to the needs of the business so the company gets the full benefits of its analytics initiatives.

Watch the Chalk Talk with David Lyle, Informatica VP Product Strategy, and then join the discussion at @leanlyle.

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Customer Success Stories

Tinkoff Bank

Tinkoff Bank acquires and retains more customers at a lower cost with Informatica Big Data Management.

Western Union

Western Union built a data platform based on Hadoop and Informatica Big Data Edition

M.D. Anderson Cancer Center

Informatica empowered scientific and clinical collaboration at this renowned cancer center by turning data into knowledge and facilitating self-service business intelligence

Related Products & Solutions

Big Data Management

Achieve faster, more flexible, and more repeatable data integration, governance, and security on Hadoop.

Big Data Parser

Access the most difficult data and file formats in Hadoop, reducing the time and cost of developing data parsers.

Vibe Data Stream

Efficiently manage all forms of streaming data so you can analyze and act on it while it's still fresh and relevant.

Relate 360

Ensure the success of big data analytics projects by uncovering accurate relationships among connected data.

Master Data Management

Delivers reliable business-critical data so you can optimize operations and make more informed decisions.

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