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Verta Insights Study Reveals that Fewer than Half of Companies Are Ready to Scale Real-time AI Within Three Years

Verta Inc., a leading provider of enterprise model management and operational artificial intelligence (AI) solutions, released findings from the 2022 State of Machine Learning Operations study, which surveyed more than 200 machine learning (ML) practitioners about their use of AI and ML models to drive business success. The study was conducted by Verta Insights, the research practice of Verta Inc., and found that although companies across industries are poised to significantly increase their use of real-time AI within the next three years, fewer than half have actually adopted the tools needed to manage the anticipated expansion.

Real-time, Real Value: 80% of Businesses See Revenue Increases Thanks to Real-time Data

KX and the Centre for Business & Economics (CEBR) have published ‘The Speed to Business Value’ an industry report showing the commercial and operational benefits to be gained by businesses adopting real-time data analytics technologies.

Analyze-then-Store: The Journey to Continuous Intelligence – Part 6

This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.

Analyze-then-Store: The Journey to Continuous Intelligence – Part 5

This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.

Analyze-then-Store: The Journey to Continuous Intelligence – Part 4

This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.

Analyze-then-Store: The Journey to Continuous Intelligence – Part 3

This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.

Analyze-then-Store: The Journey to Continuous Intelligence – Part 2

This multi-part article series by our friends at Swim is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.

Real-Time Analytics from Your Data Lake Teaching the Elephant to Dance

This whitepaper from Imply Data Inc. explains why delivering real-time analytics on a data lake is so hard, approaches companies have taken to accelerate their data lakes, and how they leveraged the same technology to create end-to-end real-time analytics architectures.

Introducing Apache Druid

Sponsored Post Apache Druid was invented to address the lack of a data store optimized for real-time analytics. Druid combines the best of real-time streaming analytics and multidimensional OLAP with the scale-out storage and computing principles of Hadoop to deliver ad hoc, search and time-based analytics against live data with sub-second end-to-end response times. Today, […]

Manage Deploys MemSQL for Real-Time Analytics

MemSQL, provider of the database platform for real-time analytics, revealed that Manage, a leader in programmatic mobile marketing and advertising, has deployed MemSQL to power real-time analytics. Manage helps enterprises like Uber, Wish, and Amazon manage global mobile marketing campaigns by buying real-time programmatic inventory to drive the most engaging users to mobile applications.