divyanshikulkarni's Journal

 
    
28
Aug 2024
8:42 AM IST
   

Learn Data Science, Big Data, and Data Analytics Concepts and Applications

Are you confused about the difference between data science, big data, and data analytics? Then USDSI� brings a detailed guide explaining their intricate differences, roles, and importance in the world of data science.

Now all organizations, whether they are start-ups or already established, are actively adopting data science technology into their business to boost their productivity and stay ahead of their competition. This has led to an increase in the data science market size which is expected to reach around $322.9 billion by 2026, as predicted by Markets and Markets.

This means, the demand for skilled data science professionals is also going to increase. If you are looking to make a career in data science, then it is important to learn the difference between these three big data science terms.

In a nutshell, here’s how they differ:
  • Data science: it is the process or technology that encompasses various tasks and processes required to convert raw data into actionable insights and build efficient data models to solve business problems.
  • Big data: Big data refers to the huge amounts of data that act as the fuel for data science models. These data can be in petabytes or zettabytes
  • �Data analytics: it is the process of all the statistical and mathematical processing required to identify trends and patterns within the data.

If you find these basic differences useful, you may be interested to learn the complete roles, applications, and tools used in these processes.

So, download your copy of this detailed guide, and enhances your understanding of these data science terms.
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