The shift in business information trends, and the role of the data scientists, comes from as new report from Gartner. The headline is that by the year 2019, self-service analytics and business intelligence tools may well be producing more reliable outputs and data analysis than data scientists can deliver. The report is titled “How to Enable Self-Service Analytics and Business Intelligence: Lessons From Gartner Award Finalists.”
Self-service analytics and business intelligence tools are designed to automate functions related to data mining. Many of these functions are typically performed manually by data scientists, with the support of machine learning platforms and data mining tools. In terms of shifting approaches to such analytics, Gartner Inc. has undertaken a survey of over 3,000 Chief Information Officers worldwide.
The survey results indicate that business intelligence is the next big topic for larger businesses, in terms of data processing. This is reflected in the way that organizations are increasing the application of self-service analytics to decipher patterns, to look for correlations, and to assess customer preferences.
Commenting on this sea change, Carlie J Idoine, Research Director at Gartner stated: “If data and analytics leaders simply provide access to data and tools alone, self-service initiatives often don’t work out well.”
He adds: “This is because the experience and skills of business users vary widely within individual organizations. Therefore, training, support and on-boarding processes are needed to help most self-service users produce meaningful output.”
The report recommends four areas for businesses to focus on. The first is to align self-service initiatives with organizational goals. In doing so it is important to communicate the value of a self-service approach throughout the organization. The second approach is to ensure that users of business information are involved with the design and development of the future self-service.
The third aspect is to adopt a flexible, light approach to data governance. This is about finding the right balance of governance to make self-service successful and scalable. The final aspect is with developing an onboarding plan, which involves providing guidance to business leaders as to how to get up and running quickly.
