Experience Certainty : Smart People + Smart Schema

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Experience certainty: smart people + smart schema is the antidote to an Analytics data cesspool
By Maureen Peterson and Fred Christian, Analytics consultants

Tom Davenport, Director of Research for the International Institute for Analytics, explains the Analytics 3.0 era for enterprises who are wanting to become data driven.
Analytics 1.0 refers to the era where enterprises use BI to drive reporting and descriptive analytics based on simple structured data. Analytics 2.0 refers to the emergence of big data (unstructured data) and technologies like Hadoop. Data scientists emerge that foster experimentation. Visual analytics gains prominence; however, predictive and prescriptive techniques are still not the main use of
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Being successful with analytics is about having the right mindset, the right organizational model, and the right strategy.” (Gartner, 2014)
Brent Dykes, a Web Analytics evangelist at Adobe, describes the challenge of navigating analytics data without proper planning using an analogy of a swimming pool. There is a shallow and a deep end where there is no gradual slope requiring you to be either a rookie swimmer, or an experienced scuba diver. There is no in-between.
“It is common for the shallow and deep sections of a real swimming pool to be connected by a gradual slope. However, too often this sloped section is missing when it comes to how data is shared at companies. The data is only available in two depths – one for the data novice (1.5 feet) and one for the data scientist (30 feet) with a steep drop-off between the levels. As interest in data continues to grow, it is critical to create a better bridge between these depths. Organizations are discovering there’s a wider group of business users who need to explore the data more freely and deeply on their own. Like my twins, they’re eager to venture beyond the shallow end but may not be prepared to swim on their own in the deep end.” (Dykes, The age of data democratization: How to effectively share data across your business | Bloomberg, 2015)
Dykes also explains how a technology focus is incomplete: “When they see
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