We are surrounded by a huge amount of information and data generated every second. This comes from our mobile phones, the internet, stores, and more. But have you ever wondered what to do with all this data? How can we make sense of all this information? Well, this is possible with Data Visualization and Analytics.

Data visualization is a graphical representation of data to uncover patterns, correlations, and insights that might remain hidden in raw data. The term ‘Data Visualization’ may seem fancy, but it is basically a way to turn complex numbers and data points into colorful and easy-to-understand pictures.

The Need for  Data Visualization

Clarity and Comprehensiveness Meaningful conversations Discovering patterns Decision-Making Storytelling Saves Time Exploration

Advantages of Data Visualization

Misinterpretation Biased Representation Complexity Technical issues Focus on Aesthetics Excess data Limited Context

Disadvantages of Data Visualizations

Traditional methods of data analysis are not sufficient for comprehending and extracting value from datasets. Data visualization is emerging as a solution to tackle the challenges faced by big data. It allows business analysts to compress vast volumes of information into visual representations that can be comprehended in a single glance.

Data Visualization in the Era of Big Data

Tableau Power BI Ggplot2 Qlikview Python Libraries Google Data Studio

Tools and Software for Data Visualization