As humans, we have come a long way from drawing animals on cave walls to presenting data on spreadsheets for various operations involved in modern business. Thanks to technology today, everyone can be a Picasso with data. We are talking about data that talks, that narrates stories and provide insights and recommendations about the future. Surprised? Well, that’s how fast technology has matured and today, it tells more about you than what even you could guess knowing about!
What are we talking about? Well, it’s Data Visualization and the fascinating world of data, analytics and predictive intelligence represented as charts, pie diagrams, bars and heat maps – to name just a few.
If you are doing a SAS Training course, here is your quick read about data visualization.
What is Data Visualization?
Data Visualization is the pictorial or graphical representation of data, generated using machine intelligence and programmable coding. It is used by data analysts and data scientists in making key decisions to grasp a first-hand insight into various dimensions of data, both structured and unstructured types. The first prototype of data visualization could be attributed to cartography experts who made the world’s maps and globes. Another example of data visualization is the “Periodical Table of Elements”. Since the advent of computers, with a further push from AI and machine learning, Data Visualization has opened up new avenues and Greenfield markets for businesses of all types who leverage technology to ascertain, “What’s next?”
Why Understand Data Visualization?
Just because Big Data is so vast, learning data visualization techniques make sense. It helps users to convey their ideas and data analyses in a better, meaningful and interactive manner. And, you can even experiment with data to see how your resultant graphs and visualizations change.
Various departments leverage data visualization:
- To turn boring, complex data into simple visual graphics
- To build canonical algorithms for historical data analytics
- To make a predictive analysis of future trends
- To clarify and segment factors influencing an outcome, such as customer behavior, advertising budgets, marketing intelligence, sales volume, life expectancy, political outcomes and so on
- To understand the relationship between data, and adjustments in metrics affecting data sources
Techniques of Data Visualization
In a powerful training course in SAS, learners could tackle Big Data challenges using modern techniques of Data Visualization. Some of the key techniques leveraged by data science teams include—
· Mileage/Gauge Charts
· Legends and Color Theory
· Box Plots
· Heat Maps
How Data Visualization Works?
The basic components of any data visualization platform consist of a Data Source, Data Management, Relational Database, Cloud Storage, Software, Analytics and Machine Learning algorithm. Together, they provide the basic framework for creating interactive data charts. As data gets complex, data visualization becomes more advanced. A good visual, interactive design with powerful customer experience sets the bar high for any modern data visualization technique.
If you have SAS Analytics training in mind, you can count on building your career in Basic and Advanced Data Visualization techniques.