Assistive Predictive Modeling allows business users to leverage a self-serve advanced analytical tool and to enjoy complex, sophisticated forecasting and business predictions in a simple, user-friendly dashboard environment – all without the skills of an analyst, data scientist or IT professional.
Does your business intelligence solution provide true advanced analytics capabilities? Can your BI tool satisfy the needs of business users, data scientists and IT staff? That may seem like a tall order but with the right business intelligence software, you can provide predictive analytics for business users, including assisted predictive modeling that walks users through the analytical process and allows them to achieve the best results without a sophisticated knowledge of data analytical techniques.
There are numerous considerations when a business looks at upgrading or acquiring an analytical solution. One very important capability is Put n’ Play predictive analysis. Assisted Predictive Modeling and predictive analysis tools should include sophisticated functionality in a simple environment that is easy for every business user.
Oh, the confusion of advanced analytical terminology. Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Add to that, the sophisticated concepts of auto-suggest, auto-recommend, time series forecasting, causation and prediction and classification techniques and you may feel that you need a degree in data science to do your job.
To be successful in business, every organization must find a way to accurately forecast and predict the future of its market, and its internal operations, and better understand the buying behavior of its customers and prospects. With the democratization of business intelligence and the advent of self-serve business intelligence tools, organizations hope to encourage and create Citizen Data Scientists and enable the average business user to leverage sophisticated predictive algorithms and BI tools without the expertise and skill of a trained data scientist. This approach allows users who are not statisticians, data scientists, programmers or analysts to leverage self-service tools to confidently make business decisions, share data, and reports and present data in a way that allows the organization to identify trends, patterns, opportunities and challenges.
