Talena Launches ActiveRx™, Predictive Analytics Infrastructure for Big Data Management

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Talena_logoTalena, the always-on big data pioneer, has unveiled Talena ActiveRx™, a predictive analytics infrastructure designed explicitly for big data management workloads. ActiveRx addresses two long-standing challenges prevalent in data management:  how to incorporate machine learning into various workloads to accurately predict data availability, and how to turn idle backup assets into active data copies. ActiveRx is available in Q2 for early access and will be generally available later this year.

Companies expect real-time insights on all aspects of their big data infrastructure to maximize customer satisfaction and revenue,” said Nitin Donde, Talena’s Founder and CEO. “Talena ActiveRx highlights the future of data management in which companies deliver an always-on data experience by mitigating the impact of unpredictable workloads and transforming idle data assets into active clusters.”

Historically, data management products have relied on passive views into data flows that deliver “hindsight” analytics, like reports and dashboards, but today’s complex, big data world requires an entirely new approach. Companies are managing much larger data volumes and data types, and have exponentially larger groups of users interacting with that data, resulting in less predictable data management workloads and application usage. Additionally, when executing larger-scale analytics jobs on big data environments companies must manage inevitable production cluster performance issues and potential data sprawl from data copies.

The rapid rise of big data applications is changing how companies protect and manage the availability of data throughout the application lifecycle – concurrently, we are acutely more aware of the tremendous business value that all data holds,” said Nik Rouda, Senior Analyst, Enterprise Strategy Group. “Talena’s ActiveRx represents a major advancement in analytics and big data management, especially for those looking to manage big data workloads.”

To address the natural consequences of big data growth, Talena ActiveRx delivers two powerful and complementary analytics components:

  • Prescriptive platform analytics based on machine learning algorithms that enable companies to make smarter decisions about their data management infrastructure leading to lower operating costs, better SLA compliance, and faster decision-making. Examples include identifying best times to run backup jobs and forecasting lapses in internal service level agreements for recovery time and recovery point objectives (RTO/RPO).
  • Active copy analytics which allow customers to transform their idle backup copies into valuable data assets. Companies can invoke rich visualizations that span Cassandra, Hive, Spark and HPE Vertica or run custom code on these data copies. By delivering an integrated compute plus analytics infrastructure, Talena ActiveRx enables companies to save considerable resources and eliminate the need to make multiple copies of data.

The intuitive ActiveRx UI requires little set up and training, allowing teams to realize cost- and time-saving benefits immediately.


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