Advanced analytics software provider Mode today announced the availability of its first instant, responsive data engine, Helix.
Helix creates the dual backbone between modern business intelligence and interactive data science. By combining these workflows, data scientists no longer have to choose between shipping fast, one-off answers and building dashboards for broader coverage.
With Helix, stakeholders can extend any analysis to answer their own questions, which means neither stakeholders nor data scientists have to predict what they'll be asked next. Regardless of the complexity of the problem at hand, users can increase the speed of better decision-making with Helix.
With Helix, Mode is further enhancing workflows for data scientists and stakeholders and making it faster and easier than ever to make informed, data-driven decisions.
Helix is a high-performance, in-memory database designed for filtering, aggregating, and manipulating query results with sub-second latency, able to visualize 2000 times more data than previous limits.
By offloading data processing from a customer’s data warehouse into a data engine designed for filtering and aggregating, Mode can deliver results faster and at a lower cost than a warehouse alone.
“From the beginning, Mode’s been on a mission to remove friction from a data scientist’s day,” said Derek Steer, CEO and co-founder of Mode. “We’re a long way from having AI powerful enough to answer the really tough questions facing companies today. But the humans we rely on to help tackle these questions are often stuck doing rote work—creating yet another dashboard. Helix dramatically accelerates everything data scientists do by automatically making their work more accessible and extensible. Creating dashboards and answering follow-up questions becomes faster and easier, so they can focus on the tough business problems they were hired to solve.”
The key benefits of Helix include a streamlined workflow for analysts and data scientists and interactive, drag-and-drop visualization tools for deep post-query exploration.
For more information about this news, visit https://mode.com.