We all have data, sometimes far too much of it. What now?
Back in high school, I recall endless hours of careful transcription of data onto graphs - indicating points and axes was quite an art and he who could draw a smooth free-hand line of best fit gained much credence. Now we have data visualisation (aka charting) tools and can show it in pie charts, bar charts, bubbles, lines, arrows and even stacked clip art images.
While such tools are useful it tapping into the strength of the human brain to see visual patterns (which are not so obvious in a column of numbers), it can still be hard to separate out the underlying trend from the detail.
SimpleCube may be able to help here as its prime interface uses summary data allowing a degree of removal from the detail. The detail is still there and can be used, but SimpleCube allows us to slice the data, using summary statistics to examine trends and overarching patterns.
For example, if you have a list of sales showing region, salesperson, item, cost and date. It would be easy to draw charts in a spreadsheet showing the sales for each date, but what if we wanted to slice the data to show sales totals by region and then by date; or count how many sales were above a certain amount and then slice by region?
A spreadsheet program could do this with a bit of manipulation, but if we had to do this many times or try out other combinations, it would get quite tedious. SimpleCube makes this easy with a drag and drop interface.
Once we have the figures, SimpleCube can then show these in charts and can also apply statistical tests to the displayed data (these are "live", so changing the clustering and filtering of the data immediately reflects in the statistical model).
A school may want to explore how many students gain marks in the top 8% of the cohort, do this for each subject, then see if there are any trends over the last few years. Another may have done that and want to see if simple measures of student ability correlate with the number in the top 8%. SimpleCube's powerful OLAP cube and statistical engine allow these "what if" questions to be answered in the time it takes to drag a few fields into position on a grid.
Please download the Demo version and work through some of the "How To" documents to get a sense of just how powerful a tool this could be for you in your data analysis scenario.