Quick Summary of Citizen Data Science blogs

Citizen Data Scientist – why not stay by Data Scientist only?

  • Data Scientist is no longer sufficient to keep up with increasing amount and variety of data
  • Citizen Data Science to empower all employees to develop their own insights
  • A business is not a homogeneous thing – data scientist has limited expertise of the business whereas the many employees do not

How will “the Citizen” change the world?

  • Data increasingly necessary for businesses to keep the edge on competition
  • Insights from data can significantly improve business; Tesco case study
  • Data Scientist incapable of having hyper localised knowledge that managers have
  • Citizen Data Scientist equipped with the right tools to develop good data insights informed by his localised business knowledge (i.e. highly relevant)

What are the barriers to adoption of Citizen Data Science?

  • Two main barriers – citizens and technology
  • Citizens – not knowledgeable, difficult to train
  • Technology – difficult to dumb down ease of use while retaining analytical prowess
  • Legacy Processes – mainly for big companies; legacy software, legacy decision making, legacy workforce

What types of companies will develop Citizen Data Science into commercial products?

  • Mainly two – analytics first and data first
  • Analytics first, then data – traditional approach, many companies, successful and going strong
  • Data first, then analytics – Salesforce leveraging its CRM platform

What competences will companies need in order to develop and commercialise Citizen Data Science?

  • Three main – Security, User Experience, Advanced Analytics
  • Security – because ever-increasing attempts at hacking; customers conscious of their personal data
  • User Experience – ease of use, enjoyable working experience
  • Advanced Analytics – necessary backbone, important to increase analytical power and ease of use at the same time

Where will the competition come from?

  • 5 leaders of Advanced Analytics
  • Competition to emerge from anywhere – open-source projects utilising community as a proof of that

What existing companies or industries might “the Citizen” disrupt?

  • Three examples – Data Analysis Consultancy Services, Statistical Software Packages, Internal Processes
  • Consultancy Services – expensive, takes long time, disconnected from everyday working of the company
  • Statistical Software Packages – might lose competition on Advanced Analytics insights to newer solutions
  • Internal Processes – clumsy, IT-centric, missing out on business expertise of other employees
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