Company Earns Highest Scores of any Vendor in Current Offering and Strategy Categories

Talend (NASDAQ: TLND), a global leader in cloud integration solutions, today announced that Forrester Research recognized the company as a Leader in its newly published report, The Forrester Wave™: Big Data Fabric, Q2 2018.

Talend earned the highest scores of any vendor in the report in both the Current Offering and Strategy categories, two of the three high-level categories Forrester evaluated. Forrester also noted that the Talend platform “simplifies the process of working with Hadoop and Spark distributions as well as new technologies like serverless computing and containers.”

Big data fabric is defined by Forrester as an emerging platform that “accelerates insights by automating ingestion, curation, discovery, preparation, and integration from data silos.” According to Forrester, the report, which is available for complimentary download, “shows how each vendor measures up and helps Enterprise Architecture (EA) pros make the right choice.”

“We are honored to be recognized as a leader in Forrester’s prestigious Wave, which we view as another strong validation of the quality and innovation of Talend’s data integration solutions,” said Ashley Stirrup, CMO, Talend. “We believe our placement in the Wave and criteria scores, speak for themselves and reinforce our ability to deliver for enterprises today and as the market continues to evolve in the future.”

In the report, Forrester recognizes Talend for supporting “real-time, batch, and dynamic data-driven use cases across on-premises, cloud, and hybrid environments.” Talend earned the highest possible scores, 5 out of 5, in six of the 12 subcategories evaluated by Forrester including Vision, Ability to Execute, and Professional Services.

According to Forrester, big data fabric can support many types of use cases, including real-time insights, machine learning, streaming analytics, and advanced analytics. It offers EA pros the ability to orchestrate data flow and curate data across various big data platforms (such as data lakes, Hadoop, and NoSQL) to support a single version of the truth, customer personalization, and advanced big data analytics — with zero or minimal coding.