Businesses to rely more on software than on scientists for analytics
GARTNER predicts that by 2019, the output of self service analytics and business intelligence (BI) software will surpass that of data scientists.
Self-service analytics and BI vendors such as Teradata, Tableau, Qlik, SAS are winning big with enterprises seeking new ways to make sense of the data they’ve captured about prospects, customers, and partners. They provide a great user interface and dozens of easy ways for businesses to train their managers, lowering the dependence on data scientists for insights.
Through their software, these vendors empower business users to study their data, gain new perspectives on the organization’s transactions, and produce actionable insights for themselves and their teams.
“The trend of digitalization is driving demand for analytics across all areas of modern business and government,” said Carlie J. Idoine, research director at Gartner in a recent press release. “Rapid advancements in artificial intelligence, Internet of Things and SaaS (cloud) analytics and BI platforms are making it easier and more cost-effective than ever before for nonspecialists to perform effective analysis and better inform their decision making.”
“If data and analytics leaders simply provide access to data and tools alone, self-service initiatives often don’t work out well,” said Ms. Idoine. “This is because the experience and skills of business users vary widely within individual organizations. Therefore, training, support and onboarding processes are needed to help most self-service users produce meaningful output.”
To help businesses along their self-service analytics and BI journey, Gartner suggests focusing on four key areas:
Align self-service initiatives with organizational goals and capture anecdotes about measurable, successful use cases: Doing so builds confidence in the approach, brings continued support, and encourages more business users to get involved.
Involve business users with designing, developing and supporting self-service: This is the best way to forge and preserve trust between the IT team and business users, ensuring the collaboration required to make such a project successful.
Take a flexible, light approach to data governance: Casual users tend to steer away from strict, inflexible frameworks – however, governance is also critical. Businesses must therefore find a way to strike a balance.
Equip business users for self-service analytics success by developing an on-boarding plan: A formal on-boarding plan helps automate and standardize the process, making it truly a ‘self-service’ function across the organization.