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Why Data Science has a ‘last-mile’ problem

Finding the right insight at the right time isn’t easy. The sheer volume of data can be overwhelming, and seldom are the questions we ask straightforward to answer.

People who work at the interface between data, technology and business are commonly referred to as Data Scientists. Gaining the skills and experience to become a data scientist takes many years of university study and practice.

Much of the work of a data scientist is devoted to the creation of predictive models. This calls for the application of statistical theory, but more so the development and application of machine learning algorithms and other computational methods. Model outputs, reflective of the research goals, usually take the form of predictions, summary statistics, and data visualisations.

A central tenet of the data science value proposition is that model outputs can be interpreted and applied within a business context. This step is the most critical link of the data science value chain, because it’s the point where people must apply their own qualitative judgements to determine the relevancy and meaning of the information produced. It requires much skill and effort, and is commonly the step that data scientists and business people find most challenging.

The biggest pain-points people encounter at this step are:

Some data science teams are looking to solve the data science bottleneck problem by using automated machine learning technologies that make the process of building and testing predictive models faster. However, these investments — while freeing up scarce data science resources — don’t address the wider organisational challenges of making data science and analytics a mainstream business capability.

The reality is there remains a “last-mile” problem with the interpretation and application of data science outputs by business people – which in turn limits the business value that can be generated by data science overall.

So how do we solve this Last Mile problem with software?

DeepConnect is the first company to make organisation-wide learning through big data analysis a core business competency for medium and large sized enterprises. The DeepConnect solution extends insight generation as a core capability throughout the enterprise, as near to the people who are asking the questions and have the domain expertise.

Best of all, we believe it’s through these technology and mindset shifts where the most exciting opportunities for insight discovery will emerge.

To learn more about our DeepConnect platform, methods and training solutions, please contact us, or check out our Leadership Academy program.