October 14, 2013 Leave a comment
Finally! :) time to briefly introduce our SmartCharts app for Excel now available at Office Apps Store (download here).
So, yet another “chart” app/tool for Excel…what’s the point? :) what’s it for?
Well, beyond being a DevScope research project and a place where we will be test driving lots of #dataviz features using the latest technologies, there were some other drivers to build the app:
- There’s so much data available these days, but still most people can’t even acknowledge that there’s lot of hidden value in data, being it small, medium or big data… so they don’t even start exploring it :(
- Provide a data discovery tool that keeps user focus on the data, not modeling, not chart designing, just slice, dice & visual data mining
- There are a lot of patterns for dataviz, but there seem to be a lack of reusable pre-built analytic models for the most simple data intelligence tasks, time series, pattern recognition, drill down views
- We are building an excessive number of dashboards (really! we are), repeating the same patterns over and over again, same for data mining… can’t we get reusable analytic modules that quickly adapt to different datasets? Data+Services inter-connectable through already available metadata?
- An Excel app seemed an awesome way to continue the research work we started with our Data Insights addin few months ago (same core concepts really, we will be back to that eventually ;) )
- A tool that we can now use to quickly & easily explore small datasets instantly in Excel (under 100k,150k rows) all kind of log tables, log streams, etl logs, usage logs.
- (yes, do not expect much value if you’re using it with small tables, or tables without time/date fields) it’s a data discovery tool, not a chart designing tool
All these are of course “experimental hypothesis” that we can now test and research (and already collecting lots of useful feedback :) ).
And stay tuned, we will be releasing some new features this week ;). Download it now & get us some feedback.
Finishing this post with a few typical usage scenarios, these are from real data , loaded the app with different tables I regularly check (clickstream logs, usage logs, etl logs, ssas query logs,…)
(some values masked, sorry!)
Integration load resource usage (~80k rows dataset)
(side note that the first time I loaded this data on the app I immediately found that I was completely unaware on where integration load resources were being spent, and how that patterns were evolving over time)
Integration loads vs extracted rows
Drill down view of integration time over time
Time of day patterns (integration times)
Time of day patterns (rows extracted)
Now a completely different dataset(120k rows), obtained from an analysis services query trace table log, instant insights: (again note that no modeling or chart designing was necessary…just click, load & explore)