Pentaho Debuts on Gartner Magic Quadrant for Data Integration Tools
Donna Prlich I Chief Product Officer, Pentaho
At Pentaho, we pride ourselves on being data challenge agnostic when it comes to the technologies and data sources customers can leverage to achieve analytic business outcomes. Doing this means our customers are freed from the hindrances of data and continue to increase analytics insight as they drive towards strategic initiatives.
Pentaho started a journey over 5 years ago as a thought leader and innovator in the big data integration and analytics market. Our open source foundation spurred an early understanding of the impact of both Hadoop and the corresponding emergence of Data Lakes to the Business Intelligence market. We had a vision that the two worlds of data and analytics would inevitably blur. Business pains would emerge front and center, while tools and technologies would be applied to the pain as opposed to the choice of the tool being the imperative. In the same way, there is a strong consciousness in the Gartner research that the convergence of cloud and big data, as well as machine learning and emerging IoT, are setting up the same complexities we saw 5 years ago—and we need to be prepared for them. Pentaho will once again, with the backing of Hitachi, be well prepared for these emerging demands.
This is why we are excited to be recognized today—for the first time ever— by Gartner, Inc. in the 2017 Magic Quadrant for Data Integration Tools. As data integration grew to become the greatest challenge in any analytic deployment, it was a logical outcome for us to be recognized for our investments in Pentaho Data Integration. More importantly, we have the proof points from our customers who achieve real world outcomes with Pentaho solving for these data challenges.
Our vision is to create a single analytic data workflow for our customers—regardless of data size, workload and use case. Pentaho 7.1, built on this promise by allowing adaptive execution on ANY engine—starting with Spark—for big data processing, in order to future proof our customers from emerging engines and prepare them for the mass and types of data involved with current big data and future IoT implementations. We also expanded cloud integration with Microsoft Azure; enterprise-level security for Hortonworks, and improved the ability to “spot check” data visually.
Industries such as healthcare, automotive and manufacturing are applying Pentaho for big data integration and analytics to become digital leaders in their industry. As a proof point, in June, we announced 2016 bookings growth in IoT analytics of 134 percent, with Pentaho customers such as BEONTRA, Caterpillar Marine Asset Intelligence, Hitachi Rail Europe (HRE) and Hyosung Corporation. This is a testament to the premise that IoT business value will only be unlocked with capabilities that address both machine generated data AND existing corporate data.
We believe today’s inclusion in the Gartner Magic Quadrant for Data Integration Tools further validates our proficiency in complex data integration. Thanks Gartner for now recognizing the important work we’re doing here at Pentaho.
To view the report, go here.
The market for data integration tools includes vendors that offer software products to enable the construction and implementation of data access and data delivery infrastructure for a variety of data integration scenarios. Gartner analysts evaluate technology providers on their ability to execute and completeness of vision.
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, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Donna Prlich, Chief Product Officer at Pentaho
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