
TIBCO Software Inc., a global leader in integration, API management, and analytics, today announced it has been named a Leader in Gartner’s 2019 Magic Quadrant for Data Science and Machine Learning Platforms. In Gartner’s latest report, the company improved its position compared to the previous year, now recognized in the Leaders quadrant. Previously, TIBCO also scored in the top quartile for product refinement, business exploration, and advanced prototyping use cases.*
“We are delighted to be recognized as a Leader in Gartner’s Magic Quadrant for Data Science and Machine Learning Platforms,” said Thomas Been, chief marketing officer, TIBCO. “We believe our position in this report reflects our dedication and distinctive ability to help customers optimize collaboration, integration, and operationalization to fully realize the value of their data science initiatives.”
Gartner notes that “Leaders have a strong presence and significant mind share in the data science and ML market. They demonstrate strength in depth and breadth across the full data exploration, model development and operationalization process. While providing outstanding service and support, Leaders are also nimble in responding to rapidly changing market conditions. The number of expert and citizen data scientists using Leaders’ platforms is significant and growing.”
Gartner continues, “Leaders are in the strongest position to influence the market’s growth and direction. They address the majority of industries, geographies, data domains, and use cases, and therefore have a solid understanding of, and strategy for, this market. Not only can they focus on executing effectively, based on current market conditions, but they also have solid roadmaps to take advantage of new developments and advancing technologies in this rapidly transforming sector. They provide thought leadership and innovative differentiation, often disrupting the market in the process. Leaders are suitable vendors for most organizations to evaluate. They should not be the only vendors evaluated, however, as other vendors might address an organization’s unique needs more precisely. Leaders provide a benchmark of high standards to which others should be compared.”
To read Gartner’s full evaluation of TIBCO, download a complimentary copy of the Magic Quadrant for Data Science and Machine Learning Platforms, (Carlie Idoine, Peter Krensky, et al., 28 January 2019) report here.
Visit TIBCO’s booth and hear its thought leaders present at the upcoming Gartner Data and Analytics Summits in Sydney (18-19 February; booth #PREM4), London (4-6 March), Orlando (18-21 March), and São Paulo (29-30 May).
*Gartner, Critical Capabilities for Data Science and Machine Learning Platforms, Peter Krensky, Carlie Idoine, et al., 4 April 2018.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.


Archive
- January 2021(44)
- December 2020(53)
- November 2020(59)
- October 2020(79)
- 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(26)
- September 2019(24)
- August 2019(15)
- July 2019(24)
- June 2019(55)
- May 2019(82)
- April 2019(77)
- March 2019(71)
- February 2019(67)
- January 2019(77)
- December 2018(46)
- November 2018(48)
- October 2018(76)
- September 2018(55)
- August 2018(63)
- July 2018(74)
- June 2018(64)
- May 2018(65)
- April 2018(76)
- March 2018(82)
- February 2018(65)
- January 2018(80)
- December 2017(71)
- November 2017(72)
- October 2017(75)
- September 2017(65)
- August 2017(97)
- July 2017(111)
- June 2017(87)
- May 2017(105)
- April 2017(113)
- March 2017(108)
- February 2017(112)
- January 2017(109)
- December 2016(110)
- November 2016(121)
- October 2016(111)
- September 2016(123)
- August 2016(169)
- July 2016(142)
- June 2016(152)
- May 2016(118)
- April 2016(60)
- March 2016(86)
- February 2016(154)
- January 2016(3)
- December 2015(150)