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IBM analytics helps Mother Teresa university drive smarter education

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Mother Teresa Women’s University, a public university, established in 1984,is using IBM analytics solution to promote academic success by training their management students on predictive analysis and reporting solutions.

The use of analytics or big data has changed the realm of technology. Big data is requiring new skills, knowledge and kinds of decision-making in every role and every profession. The university is using IBM’s analytical software, SPSS (Statistical Products and Service Solutions), to train their management students on predictive analysis and reporting solutions and to promote academic success.

IBM SPSS is a comprehensive, easy to use set of data and predictive analytics tool for users, analysts and programmers. The software offers flexible, affordable options that help colleges and universities easily integrate statistical analysis, data and text mining and survey research instruction into the classroom.

In today’s technology-driven world, we need to enhance curriculum planning by tailoring courses to different styles of learning. With the IBM solution, we will be able to better equip students with essential analytical skills to effectively transition into the professional world, said N. Kala, Registrar, Mother Teresa Women’s University”. “IBM being the leader that offers flexible, affordable IT solutions would help our institution to easily integrate statistical analysis, data and text mining and survey research instruction capabilities into the classrooms for the benefit and growth of our management students.”

“IBM has the broadest set of skills and knowledge of the industry – from technical skills to industry skills in areas such as data architects to statisticians”, said Jyothi Satyanathan, Director, Midmarket and Inside Sales, IBM India/South Asia. “IBM is working with over 200 universities around the world specifically in the area of expanding and strengthening analytics curricula to meet the growing demand of highly skilled big data business workers of the future.”

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