Knowi Releases Natural Language BI 2.0 and Brings Augmented Analytics to Anyone

Knowi Augmented Analytics Combine BI, AI, and NLP to Create the Intelligence Needed for Anyone to Make Data-Driven Decisions

Knowi, a leader in Augmented Analytics for modern data, announced the latest release of Natural Language BI 2.0 to empower anyone with powerful Google search-like self-service analytics on any data.

As an augmented analytics platform, Knowi allows anyone from technical users, to Data Scientists, to business users to access the intelligence they need to make decisions. It combines AI and Natural Language Processing (NLP) to expose previously unseen insights on any data.

“With the release of Natural Language BI 2.0, anyone in an organization can use our search bar to ask their question and Knowi will automatically query across multiple datasets and bring back the result,” said Jay Gopalakrishnan, CEO of Knowi. “Making the user experience as simple as possible is an incredibly difficult engineering challenge but something we had to solve for our customers to take full advantage of their modern data.”

According to Garter, by 2021, conversational analytics and natural language processing (NLP) will boost analytics and BI adoption from 32% of employees to over 50% of an organization’s employees, to include new classes of users particularly in front offices.

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Artificial intelligence and NLP combined with increased data complexity are driving a new wave of disruption in the analytics market. With this latest release of the Knowi platform, Knowi dismantles the old way of thinking about analytics architectures. By eliminating ETL, Knowi simplifies complex data pipelines and opens up new approaches enabling employees with data.

With Knowi augmented analytics, organizations transform to data-driven 10x faster by instantly connecting to any data, anywhere. This agility allows for rapid experimentation and easy adaption to change.

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The Knowi platform delivers this by natively accessing all your data, regardless of structure, location, or source, eliminating the need for ETL. In our data as a service layer, you can dynamically blend data across any number of disparate data sources to create the widest possible datasets. Those datasets are exposed to business users through dashboards where they can use Natural Language BI to ask any question of their data.

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