Data Science And Allied Disciplines

Data Science and Its Current Impact on Industry

The proliferation of data management systems along with the tremendous progress made over the past decade in terms of computing power have contributed to the formation of a new discipline at the intersection of Computer Science and Applied Mathematics: the Data Science domain. The main objective of Data Science as a discipline is to develop mathematical model and their computational solutions so as to enable analysts to reason and interpret massive amount of data where 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 the 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. Conveniently, Data Science comes to their rescue. Applied Data Science aims to achieve two main goals. The first 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 by 2018 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. 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., inspired from the emerging needs of industry towards addressing the new digital sciences era (Big Data) and forming the new generation of Data Sciences, introduces a number of scientific educational programs covering various aspects Data Sciences including Data Management, Big Data Analytics and Data Visualization.

About the Courses

The students of these courses will have the opportunity to gain and solidify knowledge of the most important contemporary methods of Data Science, and to develop understanding of practical applicability of the studied topics in business scenarios. They will be able learn how to formulate analytic tasks in support of business objectives, how to define successful analytic projects, and how to evaluate 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 in Data Science field.

Data Science Course

This comprehensive course provides training in all three aspects of data science: data management, data analytics and data visualization. It will train the students on various theory and practical tools of data science including SaS tools like Base SaS Programming, Macros, SQL, Hadoop, EGBS, EMiner, Text Miner, Content Categorizer, SaS Business Intelligence (BI) and SaS Visual Analytics (VA).

Big Data Analytics

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.

Data Management Course

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.

Business Analytics

The course deals with the theory and practice of structured data analytics using SaS tools like EGBS EMiner and various other tools like SPSS, R Programming Language and Microsoft Excel.

Data Visualization

This course teaches how to explore data and build reports using various analytics tool of SaS. It also provides input how to build queries in SaS Visual Data Builder. SaS tools like BI and VA will also be taught.

Career Opportunities

The course presents exciting opportunities in pursuing careers as data scientists, data professionals and data analysts in variety of sectors including financial services, retail, marketing, customer and business intelligence. On completion of the course, graduates should be equipped with sought after specialist knowledge and skills by industries which deal with acquisition, management, analytics and visualization very large volumes of data.

Leading innovation companies in the new digital era rely on mining, understanding, interpreting of such data towards content-creation, product development and new services.

Certification

On successful completion of the courses, the participants will be provided with Participation Certificate jointly provided by Calcutta Business Scholl and SaS Institute. They will also become eligible for appearing in the International Certification Examination conducted by SaS

Apply Now (Use the Long Application form for admission to EDP / MDP programs. Please note that there is no application fee.)

For More Details Call

Manali Chakraborty : +91 93304 53325

Pramit Ghosh : +91 83348 72859

MDP cell at Calcutta Business School : +91-33-2420-5225 / 5233 / 5239

E-Mail : mdp@calcuttabusinessschool.org


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Copyright © 2013 SAS Institute Inc. Cary, NC, USA. All rights reserved.

The entire Program Structure, Program Plan, and Courses offered by Calcutta Business School are Copyright © 2013 of Calcutta Business School. All Rights Reserved.