Big Data

A great post by David Rosen of Tibco on Big Data

In last week’s post, I referenced APT and FoundryDC founder Jim Manzi and his approach to Big Data. Jim spoke at the TIBCO London office digital transformation event a couple of weeks ago on the topic of “Kinda Big Data”—the compelling point that the vast majority of businesses are best served by focusing on the large sets of traditionally stored customer and transactional data. These data provide incredible insight on past behavior as predictors of customer propensity, product affinity, clusters of like-behaving individuals, and fact-based insight. The focus on value creation within “Kinda Big Data” contrasts to the hype and anxiety that has dominated the big data discussion over the past three years.

If volume is not the primary driver of digital transformation and its impact on customer experience, which “V” should we focus on: veracity or variety? In a fast data world , especially one where younger consumers are increasingly becoming the focus of retail, product, and financial companies and their marketing-experience teams, velocity is the missing attribute.

High-velocity data adds context to the powerful insights that emanate from Kinda Big Data.

In an Harvard Business Review blog post, Jess Neill makes the case for big data requiring the addition of big context. Neill discusses adding a very human element to interpretation of data, what Jim Manzi recognizes as the third leg of the technology-analysis-strategy stool. The connection from data analysis to contextual decision making is a realization that what people say and what they will do (I’d argue what we quantitatively predict and what they’ll do) is strongly driven by real-time situational variables that rarely enter into traditionally-stored data tables.

Can you read the rest on LinkedIn:

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