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There may not be much a difference between big data and it's science yet, it has always instigated the minds of many and put them into a dilemma. In this blog, we will cover the real difference between these two terms in detail. We will start with what each of them mean.
An evolutionary extension of statistics that deals with large volumes of information with the help of computer science technologies. It has played a significant role in the expansion of artificial intelligence, Machine learning, the internet of things (IoT), etc.
Deals with the vast collection of assorted information from various sources and is also available in standard database formats. It helps to give better insights about decision making and strategic management.
Big data is classified as structured, semi-structured, and unstructured:
While structured information is quite easy to understand, the unstructured form requires customized modeling techniques to extract information using various statistical tools and technologies.
There is quite a bit of confusion between these two subjects. Though machine learning is a subset of data science, they are not the same.
Where the former relates more with technology, computer tools, and software, the latter focuses more on business decisions.
The current trend in the information segmentation industry tends to focus more on big data rather than the science. The use of one allows businesses to observe various customer patterns, trends, and behavior, while the other adds value to a business by assisting companies in better decision making.
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