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Predictive analytics today become more and more connected with generic data mining and business intelligence tasks. While the latter two try to answer common questions and describe the status quo inside the company, predictive analytics should give the further picture of what might happen tomorrow, mainly the future trends (trend analysis) and behavioral patterns.
As companies gather their Big Data, they seek next for perfect-matching representation for it in their web report tables, charts or gauges. Most of these give a reply on common questions, like what is the sales status on region B of product A this month. The graphs can give a perspective on this historic data or even a trend. However, the major drawback of such tools is their rigidness if no interaction additional tools are added, like filtering or changing the data source.
The web-based pivot table on the contrary, becomes an essential tool if the predictive analytics data need to be quickly transposed, rotated or further split into visible pieces. Imagine such a web pivot table report (accessible right at the fingertips of your favorite browser) as Rubik’s Cube. The data inside are of different colors and mainly meaningless until you pull it all together to get a clear insight that would be important for working out the correct decision. Once the data is in the correct layout, apply filters, conditional formatting (yes, colors!) or add calculated fields.
The areas of application for olap pivot tables in such predictive analytics are really vast. They include enterprise-level day-to-day assignments like CRM, DSS (decision-support systems) for any areas, customer retention, direct marketing as well as clinical patient health analysis or production performance. Furthermore, by gathering historical data, pivot tables can further deliver value by giving ability to drill-down through time-related dimensions like years, months, quarters, weeks and days.
Tired of slow and static reports? Try introducing web pivot tables into your intranet or analytics solution. Who knows – maybe tomorrow your users will see the world in different colors.