by Angela Guess
Markus Sprenger recently wrote about the data maturity model: “Amazon and Netflix are great examples of companies that are far along on the maturity model for data. This maturity model addresses the issue of big data, and how companies can manage their data in increasingly strategic ways, turning that data into information and, eventually, knowledge.”
Sprenger goes on to examine the five stages of data maturity, starting with No Usable Data: “The theoretical base of this model is the company with little or no useful data. At this level, the company can’t run metrics, and doesn’t fully understand, let alone anticipate, customer needs. It has no useful, information-backed insights with which it can better run its business.”
Stage two is Big Data: “Companies at this stage are inundated with big data. They have a steady flow of data from both internal and external sources, but few have the tools needed to turn their data into information. Employees spend more time looking for information than analyzing. In many instances, employees give up, swamped by the flood of data… For newly founded companies seeking to create their initial data infrastructures, a first step would be to identify the data sources – both internal and external – of relevance to them. Then, they should put mechanisms to capture that data in place.”
Stage three is the Right Data: “Stage three companies use high-quality data, and apply both context and relevance to their data models. They have built corporate taxonomies and metadata that help categorize and explain data in meaningful ways, as well as explain the relationships and interdependencies among the data. A key part of achieving stage three is implementing a cultural shift within the organization that parallels the technological shift.”
Stage four is Predictions: “Companies in stage four can do more than conduct historical or retroactive analysis – they can also conduct predictive analysis. By knowing what is likely to happen tomorrow and beyond, companies at this stage can predict customer behavior and market demand.”
Finally, stage five is Strategy: “In stage five a company’s entire business model is built around its analytical models. Getting to stage five requires the development of predictive models that operate quite differently from the historical analysis in which the company has engaged up to this point. But historical analysis techniques – such as data mining – remain important for the ways in which they can inform the more forward-looking analysis that must be done.”
