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Garbage in, Garbage Out – How We Got Here and Why We Must Get Out Now

This whitepaper, “Garbage in, Garbage Out – How We Got Here and Why We Must Get Out Now,” from our friends over at Profisee, reflects on why the state of data in most organizations is as dismal as it is, and why there is such a challenge involved in demonstrating the value of trusted data available across mission-critical operations and analytics in an enterprise.

Factoring the User Into Supply Chain Data Presentation

In this special guest feature, Jono Marcus, Behavioral Insights Director and Digital Project Owner for AtSource.io, Olam’s sustainability insights platform, at Olam International Ltd., explores how behavioral science can make complex data meaningful and useful.

Be (More) Wrong Faster – Dumbing Down Artificial Intelligence with Bad Data

In this white paper,”Be (More) Wrong Faster – Dumbing Down Artificial Intelligence with Bad Data,” our friends over at Profisee discuss how Master Data Management (MDM) will put your organization on the fast track to automating processes and decisions while minimizing resource requirements, while simultaneously eliminating the risks associated with feeding AI and ML data that is not fully trusted. In turn, your digital business transformation will be accelerated and your competitive edge will be rock solid.

How Automation Helps You Exploit the Value in Big Data

In this sponsored post, Simon Shah spearheads marketing at Redwood Software to support continued market growth and innovation for their cloud-based IT and business process automation solutions. He believes that by using automation to collect and manage your big data processes, you will truly exploit its value for the business.

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.

Analyze-then-Store: The Journey to Continuous Intelligence

In this technical blog for data architects by our friends over at Swim, we learn 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.