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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.

How to Build a Truly Data-Driven Culture in 2020

In this contributed article, Kubit CEO Alex Li, discusses how many companies call themselves “data-driven” but often aren’t. He outlines 4 damaging moves, from data quality missteps to ignoring benchmark analytics — the most common and most perilous mistakes he’s seen businesses make with big data analytics.

Are B2B Marketers Leaving Money on the Table by Ignoring B2C Data?

In this contributed article, Collin Dayley, Senior Vice President Sales and Strategic Partnerships at Versium, suggests that typically, B2B data focuses on role, and firmographic information. While B2C data can reveal information providing clues to the emotional reasons and process your customers use when making buying decisions. By combining both B2C and B2B data, marketers can develop more relevant content and experiences that meet individual buyer needs. This is proven to increase the ability to contact and engage B2B buyers.