Agile business intelligence: 11 ideas to assess your self-service progress
The current excitement about self-service analytics centres around two main areas. The first is the rise of ‘citizen data scientists’, business users who are using self-service analytics to produce insights. They are drawing on a combination of their knowledge of the business, a level of comfort with analytical technology and maths, and a widening range of sophisticated but straightforward analytics tools. The second area is the availability of good self-service analytics tools—on the role of data scientists.
Over the past six months, SAS subject matter experts have expressed their views on these developments and how organisations can take advantage of them. We recommend them to anyone who wants to understand the spectrum of opportunities to drive better insights for business agility.
The widening spectrum of data science roles – a good introduction to the thinking behind the development of the role of citizen data scientists, and what it might involve. The article includes some suggestions for how this might change the role of data scientists themselves.
Are data scientists the chauffeurs of the 21st century? – citizen data scientists, supported by self-service analytics, may be the tool that allows analytics and data-driven decision-making to expand beyond an elite few companies that have access to qualified data scientists.
Citizen data scientists – would you like to correlate with me? – a response to criticisms that citizen data scientists are untrained and therefore dangerous. The author asserts that citizen data scientists have a role to play, because of their knowledge of how the business works, but that support from data scientists will continue to be necessary.
Self-service requires partnership – self-service analytics does not mean that data scientists should abandon business users to their own devices. They may need help in selecting the right data, and then working out what to do with it. Self-service is a partnership.
