Even the most sophisticated technical solution can fail if put into production without thought to the reporting needs of the users. Without user input, the system will not meet user expectations. With a thoughtful approach, you can support user need and provide a competitive advantage.
Add… time consuming and inaccurate XL models, mobility, collaboration
Visualization provides a means by which you can gain insight into your data. For some, visualization can be a report that appears in their e-mail inbox or on a web page. For others, it could be a grid of numbers with a chart in Excel. The key is to provide the correct, most efficient approach to allow users to view what there is to see.
Grids, such as tables and spreadsheets, are a simple and very powerful form of visualization, but when it comes to presenting data in volume, grids take up a lot of space—so much that you may need to scroll through subsets at a time. Because scrolling can be very time-consuming and tedious, important information may be overlooked, if ever even seen.
Other kinds of visualization can enhance users’ ability to interpret data volume. For example, the scatter plot is ideal for revealing patterns and anomalies in large data sets. Consider this example.
The scatter plot above provides a simple comparison of two metrics, by month, by location, and by product. In fact, Marketing should influence Sales in a positive fashion, meaning that we should see increased sales with marketing spend. This visualization provides immediate insight by showing both positive and negative outliers. Also, notice the y-axis, showing marketing. There are dozens of points demonstrating heavy marketing spend with little to no sales. In contrast, the x-axis shows instances where sales exist without much marketing spend. The two middle areas provide the norm and in fact, noise.
If viewing the scatter plot as a table, you would have twelve columns by nearly one-thousand rows. The challenge is simple – finding opportunity. Starting with the outliers provides instant direction. This visualization style presents that direction much more quickly than a tabular report.
Predicting the Possible
We demonstrated the value of visualization. Having the right lens through which to view your data allows for perspective and speed. Predictive analytics takes steps beyond visualization through a form of automation. It provides statistical means via analytical functions and scoring algorithms. Previously, this meant one needed a decent amount of knowledge to code a solution. For the most part, many vendors provide easier to use, graphical user interfaces, allowing most business users to leverage these functions.
Furthermore, users may now harness historical data to make better, more informed decisions with data mining or predictive analysis. This will help organizations eliminate guess work and enable scenario modeling.
In the eBook “Having a Conversation with Data”, learn what the current BI infrastructure has been and associated challenges with the traditional approach.