Self-Service Analytics Seen Overtaking Data Scientists
Self-service analytics and business intelligence tools are increasingly seen as one sure way to fill the data science skills gap. At least one market watcher thinks that approach is working.
Gartner released a market overview this week that predicts self-service analytics and business intelligence approaches will outpace the output of traditional data scientists by the end of next year. Among the facilitators of do-it-yourself analytics are steady advances in artificial intelligence, the explosion of data and data types produced by the Internet of Things and the wider access to data via cloud analytics.
Those advances “are making it easier and more cost-effective than ever before for non-specialists to perform effective analysis and better inform their decision making,” according to Gartner research Carlie Idoine.
Industry observers note that enterprise analytics modernization efforts include self-service data preparation, which is widely seen as a bottleneck in many analytics projects. Data prep and other self-service capabilities are therefore compressing the learning curve for using analytics tools.
However, the scaling and spread of self-service analytics and BI can quickly “descen[d] into chaos” if not managed properly. Hence, Gartner identifies four building blocks for implementing business intelligence and self-service analytics strategies. They include: aligning self-service initiatives with company goals; boosting collaboration by seeking input from business users; and striking the proper balance between data access and security.
Finally, Gartner recommends a developing an “onboarding” process to help new business users hit the ground running when they begin using self-service analytical tools. Formal company guidelines would help scale the introduction process, reducing the learning curve for applying new analytical tools to specific business problems, Idoine said.
A poll of more than 3,000 CIOs found they ranked analytics and business intelligence as “the top differentiating technology” for their organizations, helping to attract new investors. Still, the Gartner survey noted, “For data and analytics leaders, enabling self-service involves far more than the provision of easy-to-use tools.”
Gartner (NYSE: IT) previously forecast that the self-service data preparation software market would reach $1 billion by 2019, with adoption rates growing by about 5 percent through 2020.
While Gartner released no hard data backing its claim that output from self-service analytics would soon surpass results produced by data scientists, others note that data prep and other tools are widely available as is access to more data. The next step, according to tool vendors such as Qubole, a provider of cloud-based Hadoop services, is investing in the right tools and developing metrics for gauging progress toward what the vendor calls a “self-service data culture.”