
Leading Big Data Ecosystem Vendors and System Integrators Partner with Informatica to Optimize Business Value from Data Lakes
Redwood City, Calif., March 21, 2016 — Informatica, the world’s number one independent software provider focused on delivering transformative innovation for the future of all things data, today announced a new end-to-end solution to turn big data into trusted data assets for faster and more sustainable business value. With the Informatica Intelligent Data Lake – Informatica’s latest innovation in Big Data Management – data scientists and other business users can now find, prepare and protect data for analysis in a uniquely collaborative way that enables businesses to make decisions even faster, with managed self-service. By partnering with all the major big data ecosystem vendors and system integrators, Informatica is adding intelligence to data lakes by providing the unique insights into this data that only a leader in data management can do. According to Gartner, “through 2018, 80% of data lakes will not include effective metadata management capabilities, making them inefficient.”[1] However, Informatica’s unique metadata-driven approach now enables organizations to deliver successful data lakes, with agility, flexibility and trust.
Today, Informatica announced Big Data Management v10.1, empowering organizations to turn big data into business value by exploiting relationships between data, machines and people. The transformative innovation for business leaders within Informatica Big Data Management is the Informatica Intelligent Data Lake. Previously, business leaders were reliant on IT to access the data they required for decision making and IT was reliant on manual, labor-intensive approaches to integrate, govern and secure big data in a fragmented technology ecosystem. In response, business users have started to use self-service data preparation tools, which are limiting since they inadvertently create security and compliance risks from expanding data anarchy and proliferation.
In order to achieve sustainable business value for organizations, Informatica delivers the solution which balances self-service with governance. Unlike other solutions, the Informatica Intelligent Data Lake bridges both the business and IT gaps by providing managed self-service for business with IT governance, including the ability to find and access any data centrally and discover data relationships. Additionally, the Informatica solution prepares, catalogs and shares relevant data to derive and operationalize trusted business insights quickly.
“Business self-service data preparation with collaboration and governance controls is a key capability to increasing the agility of data-driven organizations,” said Sridhar Potineni, executive vice president, Information Technology, Jones Lang LaSalle (JLL). “At JLL, Big Data Management with an Intelligent Data Lake is an important foundation for the success of our modern data architecture and big data initiatives.”
Informatica Big Data Management provides the most comprehensive end-to-end data management solution for big data initiatives. Gartner predicts, “through 2018, 70% of Hadoop deployments will fail to meet cost savings and revenue generation objectives due to skills and integration challenges.”[2] The approach that Informatica has taken with the Informatica Big Data Management Platform is to provide a complete solution, including data ingestion, cleansing, transformation, matching, blending, governance, security and delivery, to provide the most critical capabilities for turning big data into business value. Read more about how Big Data Management has transformed the Informatica marketing department in a two-month period via leveraging the Intelligent Data Lake to gain valuable insights into customers.
This article was originally published on prnewswire.co.in and can be viewed in full here


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)