Inside Dundas BI
October 2018 Issue
In this issue, we show you some techniques for custom sorting of your data and how to use a custom total calculation. We also give you access to results from BARC's The BI Survey 18 using their interactive report - BI Survey Highlights Analyzer. You can compare top BI vendors in over 40 categories based on results from the world's largest survey of BI software users. We also want to remind you about our webinar on Tuesday, October 30th at 11 a.m. EDT - Designing Stunning Dashboards for Any Device. You can also take a look at our latest blog - Add Real-Time Analytics to Your Data Monitoring. Enjoy.
Sorting Your Data in the Most Meaningful Way
When it comes to data sorting, in most cases you want to sort by the top values or bottom values, for example to see the highest or worst offenders. In other cases, finding the best or worst value isn’t the focus as much as finding the value of a certain category and comparing it to the rest of the group. This is where alphabetical sorting can be handy, especially when a lot of categories are in the mix. However, at times, your data sorting rule requires a different logic. For example, if you want to sort high school years in order: Freshman, Sophomore, Junior, Senior. Or if you want to sort your chart where your brand is always the first on the left and then you see all the rest sorted by value. This is where custom sorting can come in handy.
Perfecting Data Tables with Custom Totals
Data tables are still one of the most popular forms of visualization for many users. It’s almost as if sometimes users need to first see their data in a table just to better understand the data shape, and then re-visualize it to another visualization that can better highlight trends and patterns. Whether you like it or not, if you need to design a table, adding totals to that table, either by row or by column or both, can go a long way. More often than not, the most important attributes you can add to rows and columns, are "totals", which point out the magnitude of the data. But adding totals isn’t always that straight forward. Sure it’s simple if you're just summing up a quantity measure, but what if you are trying to show the total percentage of a percentage measure?