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On a daily basis, an enterprise stores a huge amount of data onto the Cloud which may or may not be structured for future use. Analyzing such data for economic storage is always a big task and therefore, the role of a data scientist has evolved in the recent times. CoreIT looks at the role of data science in an enterprise and its value towards a business.
So, what is Data Science?
In the simplest form data science is all about using available data in creative ways to generate business value. Of all the data that is stored in the Cloud, data science deals with data inference, algorithm development, and technology to solve complex problems.
Data science includes probability models, machine learning, signal processing, data mining, statistical learning, data engineering, visualization, pattern recognition and learning, uncertainty modeling, computer programming and a lot more. These models or practices are used for uncovering findings from unstructured data that can be utilized to bring in a credible change to an existing workflow thereby adding value to a running business. For example, data mining helps to analyze patterns and understand the driving point of user interest and eventually using it to make decisions that are necessary for propelling the business towards a governing trend.
How does Data Science differ from Data Product?
All the above possibilities can give a clearer picture and produce what is called a ‘data product’. A data product utilizes data as input and processes that data to return algorithmically-generated results. Such data is structured with technical functionality that summarizes an algorithm and is designed to integrate directly into core applications.
Data science can give huge returns on investment - both from guidance through data insight and also from the development of data products. By harnessing the potential of data science, CoreIT believes enterprises can create apps, systems, and algorithms that power data-driven customer targeting engines making possible upcoming market opportunities before competitors.
