Data Science Vs Data Analysis ! What’s the Difference
As the world gradually becomes progressively more connected, the growth of internet-based services today has its day in the sun. More than 3.7 billion people are actively using internet services at today's time, creating more than 2.5 quintillion bytes of data—nothing wrong to assume; it's already in heaps. Did you know? These numbers are expected to grow to 180 zettabytes by the next 4 or 5 years. Such huge numbers indeed! What's more, people are showing great interest in this career and pursuing data scientist training. Good for all!!! Well, data keeps on growing! In addition, people and technology advancements never stop and wait for someone else to reap its advantages. However, by not making use of the technology available at your fingertips, you're risking way too much. Odds are, you or maybe your business is risking and limiting their growth, success, profits, and a lot more. To manage this massive amount of data with adequate consideration and efficiency, there are domain professionals like data engineers, data analysts, and data scientists to do that job. Let's explore the differences between data analysis and data science. Not so often, two of these sounds a lot similar, but there are quite separable, having dissimilar implications and meanings.