The proliferation of data management systems along with the tremendous progress made over the past decade in terms of advancements in computing power have contributed to the formation of a new discipline at the junction of Computer Science and Applied Mathematics: the Data Science domain. The main objective of Data Science as a discipline is to develop mathematical models and their computational solutions so as to enable analysts to reason and interpret massive amount of data wherein typically the information sought is quite sparse. Modern enterprise is a complex system spanning a variety of functions in pursuit of a range of convoluted objectives. Its environment is exposed to the effects of globalization and "era of information", producing an influx of large amounts of complex multi-source data that may contain useful evidence. As a result, present-day decision makers face an increasingly formidable task of internalizing huge amounts of time-critical information while being expected to always make the right decisions at the right time. This is where Data Science comes to their rescue. Applied Data Science aims to achieve two main goals: The first one is to optimize the efficiency of decision making by human managers. The second is to maximize the utilization of available data, so that no important clue is ever missed.
Moreover as the relevance of Data Science and Big Data analytics gathers momentum, it’s helping to create big career opportunities for IT professionals – if they have the right qualifications. According to a report published in 2011 by McKinsey & Co. – the U.S. could face a shortage of 140,000 to 190,000 people with “deep analytical talent” and of 1.5 million people capable of analyzing data in ways that enable business decisions by no later than 2018. Companies are, and will continue to be looking for employees with a complex set of skills to tap big data’s promise of competitive advantage, market watchers say.
Calcutta Business School, in collaboration with SaS Inc., has been inspired towards addressing the new digital sciences era (Big Data) and forming the new generation of Data Sciences owing to the emerging needs of the industry. As a result, they have introduced a number of scientific educational programs covering various aspects of Data Sciences including Data Management, Big Data Analytics and Data Visualization.
The students of these courses will have an opportunity to gain and solidify knowledge of the most important and contemporary methods of Data Science, and to develop understanding of practical applicability of the studied topics in business scenarios. They will learn how to formulate analytical tasks in support of business objectives, define successful analytics projects and evaluate the practical utility of existing and potential applications of the discussed technologies in practice. Specifically, the students will acquire knowledge, skills and expertise required for the analysis, interpretation and visualization of complex, high-volume, high-dimensional and structured/unstructured data from varying sources. The program will be delivered through activity-led and problem-based learning in the context of current state-of-the-art techniques utilized in the field of Data Science.
This comprehensive course provides training in all three aspects of Data Science: Data Management, Data Analytics and Data Visualization. It will train students in the utilization of various theoretical and practical data science tools such as SaS tools like Base SaS Programming, Macros, SQL, Hadoop, EGBS, EMiner, Text Miner, Content Categorizer, SaS Business Intelligence (BI) and SaS Visual Analytics (VA).
The course provides inputs for both theory and practice of big data analytics including analytics of unstructured and structured data using tools like SaS tools EGBS, EMiner, Text Miner and content categorizer. In addition tools like SPSS and R Programming Language will also be covered.
The course includes SaS base programming, Macros and Structured Query Language. It also includes the use of Hadoop for storing and processing big data in a distributed fashion.
This course deals with the theory and practice of structured data analytics using SaS tools such as EGBS EMiner and various other tools such as SPSS, R Programming Language and Microsoft Excel.
This course teaches students the best ways of exploring data and building reports using various analytics tool of SaS. It also provides the necessary input on building queries in SaS Visual Data Builder. SaS tools such as BI and VA will also be taught herein.
The course presents students with exciting career prospects as Data Scientists, Data Professionals and Data Analysts in a variety of sectors including Financial Services, Retail, Marketing, Customer and Business Intelligence. Upon completion of the course, graduates would be equipped with sought after specialist knowledge and skills by industries dealing with the acquisition, management, analytics and visualization of very large volumes of data.
Leading innovation companies in the new digital era rely on the mining, understanding, and interpretation of such data towards content-creation, product development and creation of new services.
On successful completion of the above course, participants will be provided with a Participation Certificate jointly given by the Calcutta Business School and SaS Institute. They will also become eligible for appearing for the International Certification Examination conducted by SaS.
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