A picture can portray thousand words. The goal of data visualization is to draw attention of analysts and managers to focus on the part of data where the action is required. Exploring large data sets with big pivot tables is forcing users to study all of the data available even though that there is no action required.
A simple example where an analyst wants to study 20 different markets, 30 product groups through 12 months might already be a challenging task. This case requires a data table with 7200 cells when using pivot tables to show all the information hidden in the data set. Visualization and data mining can display critical markets and product groups or those with highest growth rates in just few seconds.
Organizations used to work with large tables often in printed form need time to adapt new techniques and technologies. This is not always an easy task but the value of data visualization is usually quickly recognized and increasingly used over time.
Among our best data visualization examples are:
- Operations analytics for performance, stand still, quality and overall equipment efficiency (OEE)
- Warehouse management analytics
- Sales and logistics geo analytics
- Profitability analysis
- Financial and controlling analyses.