{"id":621,"date":"2018-11-08T09:24:41","date_gmt":"2018-11-08T14:24:41","guid":{"rendered":"https:\/\/treehousetechgroup.com\/?p=621"},"modified":"2021-05-20T11:30:06","modified_gmt":"2021-05-20T15:30:06","slug":"avoiding-visualization-failures","status":"publish","type":"post","link":"https:\/\/treehousetechgroup.com\/avoiding-visualization-failures\/","title":{"rendered":"Avoiding Visualization Failures"},"content":{"rendered":"\n
An important component to big data management is transforming your analytics into a visual representation that can be easily digested by stakeholders. Data visualization can be a powerful tool that has a strong impact. Unfortunately, there are also a number of ways in which data visualization can go awry.<\/p>\n\n\n\n
There have been numerous examples of data visualization fails leading to disaster, including recently a confusing chart design for an OECD study on job automation that caused media coverage to misinterpret and misrepresent the results of the study.<\/p>\n\n\n\n
To help your company avoid these visualization blunders, we\u2019ve put together a list of 3 data visualization practices to avoid.<\/p>\n\n\n\n
Too much detail<\/strong><\/p>\n\n\n\n When you are the one presenting data, you are presumably the expert on the information and have a deep understanding of the facts that support the graphics. In an attempt to demonstrate your wealth of knowledge, it might be tempting to throw as many details as possible into your visuals. However, with graphics there really can be too much of a good thing. Too many layers of information and visuals lead to confusion or frustration on the part of the viewer.<\/p>\n\n\n\n