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Differences Between Data Science vs Data Visualization

Data Science can be explained as the process of interpreting with the data to extract insights for a better decision making. The analysis process in Data Science comprises have sequence of steps like Data Mining, Data Cleaning, Data Processing, Data Model Preparation, Data Analyzing & finally Data Visualization.

Data visualization can be interpreted as the process of representing the insights from the data in an attractive visual format. In order to perform the Data Analytics process, Data Scientists need to use a lot of tools. There are several tools for performing Data Visualization & Tableau is one of the most predominantly used tool in this process.

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Understanding Data Science & Data Visualization-

To best explain the Data Science & Data Visualization, let’s consider the example of Amazon’s recommendation system in the ecommerce platform. This model makes of advanced Machine Learning algorithms to study the users web activity and interprets and manipulate it thereby presenting the users with recommendations which would surely match with his interests.

In this process of presenting the user with recommendations, the data scientists represent (visualize) the user’s web activity which is then analyzed to predict which products would be of user interest & present him/her with these recommendations. This is where data visualization comes into the picture.

Both Data Science and Data Visualization cannot be used interchangeably as they are two different terms. However, both these aspects are clearly associated to each other. Data visualization is more like a subset of Data Science. As mentioned earlier, Data Science is not a single process, it includes a number of aspects to interpret with the data to explore its insights. Data mining techniques, EDA, Modeling, representation, visualization each has its own prominence.

So if you are intended to become a Data Scientist, you need to have a clear knowledge & hands-on skills in all the multidisciplinary aspects involved in Data Science.