Data Science is the science of extracting information by analyzing data. It is a part of computer science. Data science uses principles and techniques from many fields such as mathematics, astrology, counselLing theory, informatics, etc. The development of the branch of artificial intelligence called machine learning has given new momentum and importance to the development of this field.
After All
In 1962, John Tukey described an area he called “data modification” that is relevant to today’s discussion of statistics. Later, in 1992, a study at the University of Montpellier II stated that a new knowledge was developing that was based on statistics from different types and sources, and combined the theories and principles of the time with computer calculations. The history of the term “data science” dates back to 1974, when Peter Naur introduced it as another name for “computer science”. In 1996, the International Federation of Classification Societies created the first conference that specifically presented data science as a discipline.
Why Is Data Science Needed?
Traditionally, the information we had was mostly structured and low-sized, which could be analyzed directly using BI (Business Intelligence) tools. Unlike data in traditional systems, which was mostly formatted, most information today is unstructured or semi-structured.[8]
Data Science Helps Us In The Following Tasks Like
1. Better decision making: Data science enables the organization to take data-driven decisions. For example, a retailer can analyze customer purchasing behavior to determine which products to sell together or how much inventory to keep in stock.
2. Understanding Customers: Data science helps organizations understand their customers better. They can analyze customer preferences, needs, and behavior, helping them run more targeted marketing campaigns and provide a better customer experience.
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