A Look at Computer-Assisted Features for Prep, Discovery & Analysis, Language-Based Query & Prediction 

The latest breakthroughs in business intelligence and analytics are seeing the application of heuristics, machine learning (ML), artificial intelligence and automation to improve data access and data quality, uncover hidden patterns and correlations in data, pinpoint what’s driving particular results, predict future results and suggest actions to maximize or minimize desirable or undesirable outcomes. What’s more, natural language (NL) interfaces are making it easier for business users without knowledge of data science or query languages to gain insight and make better decisions based on data.

This report focuses on the emerging “augmented” features designed to help untrained businesspeople, as well as experienced analysts and power users, gain data-driven insight and make better decisions. As this report details, augmented features can help people prepare data for analysis, discover what’s interesting about selected data sets, select best-fit analyses and visualizations, and determine what caused notable outcomes. Automated statistical and ML techniques are helping those who aren’t data scientists to see trends, develop forecasts, generate predictive models and even suggest next-best actions. NL understanding and NL generation technologies also help to humanize data analysis, supporting language-based querying and offering textual descriptions that aid users in understanding visual analyses and raw stats. 

In short, augmented analytics is computer-assisted analytics, with automations, suggestions and guided experiences complementing humans. Computers can automate repetitive drudgery, handle calculations at scale with ease and speed, and augment the interpretive skill and subject-matter expertise of employees, partners and customers.

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