You are reading the article Upcoming Trends In Data Visualization updated in September 2023 on the website Climeeviet.com. We hope that the information we have shared is helpful to you. If you find the content interesting and meaningful, please share it with your friends and continue to follow and support us for the latest updates. Suggested October 2023 Upcoming Trends In Data Visualization
Recently, we were blessed with a baby girl. Among a lot of other things, one thing which keeps mesmerizing me is the continuous change happening in the new born. In 10 days, she looks very different compared to how she looked when she was born. I am told that she will change further and I should expect changes continuously!
While these changes look apparent to a person looking at the baby after a break (say 5 – 10 days). At times, people taking care of baby day in and day out fail to notice them. On a similar note, analysts working in analytics industry day in and day out fail to notice some of the changes visible to an outsider. Thankfully, the rate of change in analytics industry is months and not days.
The aim of this post is to highlight some of the key changes happening in the way we visualize data and provide some resources to use so that you can start capitalizing on these changes. While visualization itself is a topic which deserves multiple books and blogs, the purpose of this post is to highlight some key changes happening and provide ways to prepare for them. But before we get into these changes, let’s quickly understand what’s driving these changes?
[stextbox id=”section”]Drivers for changes in data visualization:[/stextbox]
There are 3 key drivers driving changes in visualization:
Volume of data: With the data to be analyzed becoming larger every second, right visualization has become critical day by day. Gone are the days when you could scroll through the data and get a fair idea about data quality and values. While this might be scary for some analysts, increased data has created opportunities to slice, dice and represent the data in ways, which were not possible for a common analyst in past.
Increase in computational power: When I was working on my Masters thesis (8 years back), creating an unstructured grid to simulate aerodynamic flow over objects could take days. Today the same computation can be done within minutes. Similarly, visualizations which took hours in past can now be done in matter of seconds. This has enabled creating visualization which might be computationally intense. Creating visualizations to track down chains of social media discussions, their impact on website traffic and eventually customer behaviour was simply unimaginable in past due to lack of computational power.
[stextbox id=”section”]Upcoming trends in visualization:[/stextbox]
Use of maps (including heat maps) can be achieved through variety of tools and libraries. Some of them are mentioned below:
Google Maps – Simples form of charts in form of Geo charts
Qlikview / SAS and a list of other tools through add ins and extensions
Additional mapping softwares / libraries like Modest Maps, Leaflet, Polymaps, CartoDB, Kartograph, D3.js
Increased use of data mashups for exploratory analysis: Data mashups refer to tools which can import and join data on the fly. They don’t rely on the middle layers of an ETL system to import and join data before it can be used. Further, these tools have enhanced visualization capabilities to perform data exploration and discovery before investing time in predictive modelling. A lot of well-known vendors have entered this space as these tools can cut down exploration stage to a fraction of what was required in traditional tools. Some examples of these tools include SAS Visual Analysis, Qlikview etc. The picture below shows a few screenshots of SAS Visual Analytics.
Use of timeline to show evolution and changes: While there is nothing new in this visualization and it can be created even in a simple spread sheet, its application and usage has increased suddenly. Ability to show interactive visuals with better graphics has increased appeal of timelines significantly. Following is an example of visualization through time line.
In order to create timeline, you can use tools which create infographics or specialist tool like Timeline.
Creating visualization with mobile devices in mind: With increase in smartphones and smart devices, a lot of customers view these visualizations on the go. Further, penetration of mobile devices is going to increase further. So, whenever you make a new dashboard / visualization, just think how will it look on various mobiles and tablets? There are various tools, which have capability to create apps or dashboards customized for mobile devices (e.g. SAS Visual Analytics, Qlikview etc.)
If you like what you just read & want to continue your analytics learning, subscribe to our emails or like our facebook page.Related
You're reading Upcoming Trends In Data Visualization
Update the detailed information about Upcoming Trends In Data Visualization on the Climeeviet.com website. We hope the article's content will meet your needs, and we will regularly update the information to provide you with the fastest and most accurate information. Have a great day!