The human brain values visuals over any other type of information. MIT neuroscientists have confirmed that our brain can process an image in just 13 milliseconds—60,000 times faster than the speed at which it consumes text. 
Data visualization has thus emerged as key to integrated data analytics and gaining valuable business intelligence. Data visualization is no less than art supporting data science, where tabular or non-tabular data, binary codes, and text-heavy data get collected and transformed into simplified graphical representations. The graphs, maps, and charts that are visually appealing make the information easier to understand, analyze, and derive business intelligence. Data visualization can help reveal patterns and acquire insights that would not have been easily detectable in text format.
Data Visualization Techniques:
- Charts (Line/Pie/Bar)
- Diagrams and Matrices
There are many different techniques for data visualization. Some of the more popular types are:
The different data visualization techniques are used interchangeably to represent information and reveal valuable hidden patterns and insights. Since each has its strengths and shortfalls, choosing a data visualization technique depends on the data and the goal of the analysis. For example, a business analyst may use a simple bar chart to compare the results of two different Machine Learning models and their performance. However, a more granular visualization technique might help a production planner drill down into the process parameter details to discover anomalies in the production.
The Power of LIVE Data Visualization with AI/ML:
Data visualization is like the lynchpin between big data analytics and machine learning or AI apps. It helps production planners and domain experts interpret and understand what our Bodhee AI Apps have uncovered from the complex production data. When our Digital Twin creates a LIVE simulation of the shop floor realities, vivid data visualization provides 360-degree visibility of processes. That empowers the decision-makers to develop more accurate and efficient production models.
If our machine learning algorithms are fast at detecting outliers, accurate data visualization expedites the communication of actionable insights. Identifying patterns and correlations between process parameters and gaining insights into shop-floor realities would have been impossible without the simplified data visualization methods. Our AI apps also utilize well-articulated data visualization for real-time communication of results reflected in production throughput, batch quality, yield, etc.
When all production data gets integrated and visualized, organizations can also clearly communicate the findings to stakeholders. Additionally, data visualization can help present complex ideas to non-experts who need to understand the use, impact, and efficacy of AI apps for manufacturing optimization.
Drive optimized production performance with strong data visualization and AI for advanced business analytics!
 Trafton, A. (2014, January 16). In the blink of an eye. MIT News. https://news.mit.edu/2014/in-the-blink-of-an-eye-0116
 Peterman, M. (n.d.). 15 Statistics That Prove the Power of Data Visualization. Blog.csgsolutions.com. https://blog.csgsolutions.com/15-statistics-prove-power-data-visualization