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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.

From Out of Nowhere: the Unstoppable Rise of the Data Catalog

The data catalog has come from nowhere in the past five years to become a key enabling technology for multiple use cases including self-service analytics, self-service data preparation and multi-location data management. Download a new white paper from Unifi Software that explores the data catalog as a major data management breakthrough, as well as its importance in enabling modern analytics architecture.

The Data Catalog Business Case

The value and benefits of a data catalog are often described as the ability for analysts to find the data they need quickly and efficiently. Data cataloging accelerates analysis by minimizing the time and effort that analysts spend finding and preparing data.

The Future of Infrastructure Design: Data Centric Architecture

Pure Storage (NYSE: PSTG), the all-flash storage platform that helps innovators build a better world with data, unveiled its vision for the future of infrastructure – a Data Centric Architecture. With best-in-class storage purpose-built for modern workloads and challenges, Pure Storage helps “New meet Now” by continuing to deliver next-generation technology and collaborative partnerships that empower organizations to innovate.

Does It Make Sense to Do Big Data with Small Nodes?

In this contributed article, Glauber Costa, Principal Architect at ScyllaDB, busts some myths about the best node size for big data. In this age of big data and powerful commodity hardware there’s an ongoing debate about node size. Does it make sense to use a lot of small nodes to handle big data workloads? Or should we instead use only a handful of very big nodes?