Data analysis & data visualization best practices for Business Intelligence (P2)
At Yellowfin, we’ve always said that the key to an effective Business Intelligence (BI) program is sustained widespread user-adoption. Why? Because widespread user-adoption enables you to derive value from the project and realize superior Return on Investment (ROI). High levels of sustainable user adoption are achieved by making BI easy – easy-to-use, consume and deliver to end-users. The product must make it easier for users of all types to perform their daily and strategic job functions.
Good data visualizations achieve this by making data interpretation quick and easy, delivering deeper, better business insights. Poor data visualizations, that are misleading and turn data interpretation into a burdensome process, result in user drop-off, misunderstandings, less accurate and timely results, and failed ROI. For more on the correct application of data visualizations, check out our formative blog post Data analysis & data visualization best practices for Business Intelligence (P1).
Mooers’ Law applied to Business Intelligence
When considering data visualization best practices, just think of the founding American computer scientist, Calvin Northrup Mooers, and his famous Mooers’ Law of 1959:
“An information retrieval system will tend not to be used whenever it is more painful and troublesome for a customer to have information than for him not to have it.
“Where an information retrieval system tends not to be used, a more capable information retrieval system may tend to be used even less.”
What good is something, (or ANYTHING for that matter), if it’s inappropriate for achieving the desired objective, actually makes the objective harder to achieve, or you’re not using it at all? Bad data visualization can be compared to a skydiver leaping from 10,000 feet with an anvil tied to their leg.
Stephen Few: Effective visual communication of data
Also, take heed of the irreverent modern-day data visualization expert and aficionado, Stephen Few, and his philosophy espoused in Information Dashboard Design: The Effective Visual Communication of Data: “An effective dashboard [or report] is the product not of cute gauges, meters, and traffic lights, but rather of informed design: more science than art, more simplicity than dazzle. It is, above all else, about communication.”
Poor data visualization leads to user frustration, misuse, abuse, distrust, and ultimately, abandonment. Great data analysis, through highly intuitive data visualizations, leads to satisfied, active and informed users, and remarkable ROI.
The key to effective data visualization, analysis, and deeper insights? Make it easy by keeping it simple. This ensures that the data, not the chart or graph, remains the center of focus.
Today’s data visualization tip: Use color suitably and sparingly for maximum effect
The appropriate application of color can make core trends, patters and associations in a data set more noticeable and consumable within almost any type of chart. The core objective of all data visualization is to effectively display data to assist in the analysis of that data – a minimalist approach will garner the best results. Bombarding report consumers with unnecessary color will only distract and detract from the data, restrict the ability to derive meaning, and ultimately hamper the capacity to make the best decisions in the shortest possible timeframe.
Highlighting alerts in a bar chart
The bar chart below uses a simple contrast in color to highlight any values over 150,000,000.
Any value over 150,000,000 is easily distinguishable from the surrounding values in the chart, immediately drawing the reader’s attention, and prompting necessary action.
Distinguishing values in a radar chart
Contrasting colors are effectively applied in the below radar chart to help clearly separate store (blue) and online (yellow) transactions. The number and time of online and physical transactions is immediately visible.
The lightness of the yellow and deeper shade of blue are also well chosen, allowing the two values to be easily analyzed even when they intersect.
Conclusion
Aside from the overarching concepts of simplicity and purpose, there are a number of core rules that should be abided by when designing charts and dashboards for BI. The suitably sparing application of color is but one design rule that should be utilized to aid data consumption and accurate decision-making.
Stay tuned for our next data visualization tip, as we continue making data analysis and Business Intelligence easy.