Businesses competing on data must be masters of change. To keep pace with constantly shifting business models, markets, and customer expectations, companies must become more agile, which includes empowering employees with insights that are available at their fingertips.
Self-service analytics is one of the tactics separating industry leaders from laggards.
In today's world, "self-service" is no longer synonymous with passively consuming static reports pre-packaged by IT. It's more about building one's own reports, exploring data, and interacting with it.
Self-service BI and analytics solutions are continuing to evolve to meet the requirements of agile, data-driven enterprises. As a result, the vendor landscape is changing radically. So radically, in fact, that Gartner reimagined its BI and analytics Magic Quadrant for 2016.
By 2018, Gartner expects self-service to mean more than analytics. By then, most business users and analysts will have access to self-service tools that also enable them to prepare data for analysis.
While software can abstract the underlying complexity of connecting to data sources or executing an analysis, software is not a complete substitute for human intellect. Although predictive and prescriptive analytics can help, humans still need to understand how they can use data to benefit the business. In addition, specialized knowledge is still necessary to solve unusually difficult problems.
Wherever a company is on its journey, there is no shortage of tools from which to choose. But even with "the right" tools in place (which varies from organization to organization), businesses can still fail to realize the potential business value of their efforts because they still have organizational obstacles to overcome, not the least of which is balancing the pace of business and technological innovation with a corporate structure and mindset that can support it.
Here are some ways to realize longer-term value from self-service BI and analytics investments.Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include ... View Full Bio