In the 21st century huge quantities of data are generated every minute. These data are available to those who want it at a very reasonable cost. Top notch companies(not only the Fortune 500) in every sector are focusing their energies on exploiting data for competitive advantage to gain leverage over their competitors in the hyper competitive,dynamic business environment of the modern world.
In the not so distant past, firms employed teams of statisticians, modelers, and analysts to explore data sets manually, but today the volume and variety of data has far outstripped the capacity of manual analysis. At the same time, computers have become ultra powerful, networking is present everywhere, and algorithms that can connect data sets have been developed. This has led to broader
and deeper analyses of the data compared to earlier times. The convergence of these phenomena has given rise to the increasingly widespread business application of data science principles.
Data science refers to all those activities concerned with the collection, preparation, analysis, visualization, management and preservation of large amounts of information.It is not just statistics or machine learning in the context of technology industry.
The profile of a data scientist includes the following:
Computer science,Mathematics,Statistics,Machine learning, Domain Expertise,Scientific instinct, Communication and presentation skills,Data visualization.
Another way to look at data science:
The world wide web is full of applications(apps) which are data centric. One example is e-commerce. The different components include a database in the back end and middleware that communicates with a number of other databases and data services . Simply using data isn’t “data science.”
A data application acquires its core value from the data used, and in the process creates more data. Therefore it can be called a data product. Data science facilitates the creation of data products.
The revolutionary phenomenon of big data is closely linked to the emergence of data science. Benefiting from big data implies development of core teams in the organisation with this unique skill set, and making them understand the management philosophy which is the readiness of organization to comprehend
and use data for gaining an ever increasing market share to the benefit of all shareholders.
References:
1.Data Science for Business by Foster Provost and Tom Fawcett, O’Reilly 2013
2.An Introduction to Data Science:Jeffrey Stanton,Syracuse University,2012
3..Doing Data Science" Rachel Schutt and Cathy O'Neil, O'REILLY Second Indian Reprint,September 2014
4.Big Data Now :by O’Reilly Media,First Edition September 2011
5.Big Data Now: 2012 Edition O’Reilly Media