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Data science, ranked as one of the hottest selling skills on the market by the Harvard Business Review, has become a field of interest for many. Individuals, whether they are fresher or working professionals, are already planning to become a data science expert. Data is the latest gold that powers all tactics and policies. So, the one who has the data access has the expertise to control anything. But when we talk about data, we have a popular debate about Big Data or Data Science. While both of these fields deal with data, there is a distinction between the two, and we’re going to try to explain the same thing.
Big data or data science: which one is better off?
Well this is a common query that you’ll come across if you’re acquainted with data, so we’re trying to address the same thing, but before concluding, it’s necessary to explore what is big data and data science and how these two fields function.
Big Data: as can be translated by the term, Big Data refers to dealing with a vast amount of data using traditional techniques. The analysis of Big Data begins by operating on raw and unorganised data. It helps to draw inference and make better choices.
Data Science: This is an interdisciplinary discipline that deals with both structured and unstructured data. This is used to draw inferences from this data. Data Science is also concerned with machine learning, data mining and big data.
Understanding the gap between them:
Although Big Data and Data Science are used to draw inferences and results using data, it is important to understand what the difference is between the two:
• Businesses use Big Data to increase their productivity and to understand the untapped market. However, data science is essentially concerned with providing simulation techniques and methods for analysing the potential of Big Data.
• While Big Data is used to capture and analyse a vast amount of data, data science is used to derive useful knowledge from it.
• Big data is characterised by 3Vs, velocity, variety and volume, and data science offers a data processing technique.
• Big Data is a collection of data that only has meaning when processed, and data science uses both logical and realistic methods to collect knowledge from big data.
• Big Data deals with huge volumes and is called data mining, data science uses ML to develop software and models to extract information from the pile of big data.
• Data science focuses on business decisions, but Big Data applies to computing tools and applications.
From the two differences described above, we can infer that Big Data Sieves Data and Data Science deals with the evaluation of data and knowledge, thus allowing you to draw the conclusion that allows businesses to strategize their market.
So when it comes to knowing what education is important, Big Data and Data Science are linked to each other and based on your field of interest, you can choose one.
Conclusion: Global Tech Council provides a renowned learning network where you can learn about Big Data and Data Science, along with other technology such as Machine Learning, Artificial Intelligence, and so on. Data is going to rule the planet, and if you’re planning to get certification in this area, you’ll need to contact the Global Tech Council.