Over the last ten years there has been a strong trend in business intelligence (BI) and analytics being very much “self-service” but it is predicted that in 2018 and beyond, this will change. How exactly will these changes manifest themselves in the world of data and analytics?
It is already evident that there is a growing list of what is being termed as “smart” capabilities powered by machine learning (ML) and artificial intelligence (AI), and these smart capabilities are tipped to help move us beyond the limits of the self-service arena.
Changes are already evident in 5 key areas – discovery, analysis, data prep, prediction and AI-powered prescriptive applications, and there have already been a number of announcements about ML being applied to tasks such as discovering new data, data cleansing and combining and suggesting combinations of data that could uncover important insights that may have been missed ordinarily. Those who are non-technical business users may appreciate ML powered suggestions on data visualizations that are the best fit for them. Conversely, automated modelling features should help non-technical business users tap into the power of predictive analytics.
Some of these capabilities are already starting to come to the forefront, such as more advanced natural language (NL) capabilities than querying based on keywords available in column headers. These more advanced NL capabilities can discern nuances and intent in complete sentences, whether they are typed or translated with speech-to-text capabilities with voice. Systems are starting to retain the context of queries instead of asking one individual question at a time, a responsive dialogue with the data you are looking at will be possible, and you will be able to drill down and explore it from that initial query.
It is true however that many business users are more interested in action and outcomes rather than interpreting data reports, dashboards and data visualization and these are the users who are more likely to take advantage of a growing list of smart AI and ML powered learning applications that are emerging. The context of business decisions is often built into applications for supply chain, HR, marketing, sales, logistics and more and in these cases the data analytics can be fine tuned to deliver any next steps that should be taken or even automate various actions to ensure they lead to desired outcomes.
These exciting and emerging capabilities will make analytics, BI and data driven decision making much more accessible, actionable for non-technical business users and understandable, but it seems that many organizations have been slow to embrace the changes.
Have you seen any particular advances or transformation from machine learning or artificial intelligence that has transformed your data and analytics applications? Have these capabilities made integration between various departments such as sales, HR, marketing and logistics easier? Join the debate on our CxO Hangouts and LinkedIn Groups.
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