President wants transformation of academic data management
Updated: Jan 10, 2014 04:34:06pm
Kolkata, Jan 10 (KNN) President Pranab Mukherjee today asked the institutions like the Indian Statistical Institute to transform the academic management of the important discipline of data, analytics and computing.
In his convocation address at the institute, he said, “Big data, analytics and ubiquitous computing have created unique opportunities. It has led to an increase in the demand for well-trained professionals in these fields. However, as the analytic techniques are complex, they underline the need for a great deal of expertise. A large pool of competent statisticians in the country is necessary to support the analytical needs of the public and private sectors.
“Our universities and academic institutions teaching Statistics and allied subjects must take due care to up-grade the standards of instruction. I look upon a distinguished institution like the ISI to take the lead in transforming the academic management of this important discipline.”
He said it was a fact that statistical models and techniques bestow great advantage to the user. However, it is prudent to also exercise due caution in analyzing large data and drawing inferences. Capturing unstructured data and converting them into a structured format are technically challenging problems. They have to be pursued in an enlightened manner. Drawing inferences call for adequate scrutiny of the theory requiring the combined knowledge of the statistician and of the subject expert.
“In this context, it is worth remembering what Albert Camus, the French author and philosopher of the last century, had stated and I quote: ‘The evil in the world comes almost always from ignorance, and goodwill can cause as much damage as ill-will if it is not enlightened’”.
Statistical and allied techniques are depended upon by business for operational and strategic decision making. The corporate sector makes extensive use of Statistics and allied subjects like Mathematics, Economics, Operations Research, Quality Management and Computer Science. Data such as usage of social networking sites, footfalls in large retail stores, hits on websites and usage of credit cards are thoroughly analyzed for widely differing purposes like uncovering hitherto unknown consumer behaviour, assessment of risk, detection of fraudulent transactions and discovering new customer segments. (KNN/ PC)
In his convocation address at the institute, he said, “Big data, analytics and ubiquitous computing have created unique opportunities. It has led to an increase in the demand for well-trained professionals in these fields. However, as the analytic techniques are complex, they underline the need for a great deal of expertise. A large pool of competent statisticians in the country is necessary to support the analytical needs of the public and private sectors.
“Our universities and academic institutions teaching Statistics and allied subjects must take due care to up-grade the standards of instruction. I look upon a distinguished institution like the ISI to take the lead in transforming the academic management of this important discipline.”
He said it was a fact that statistical models and techniques bestow great advantage to the user. However, it is prudent to also exercise due caution in analyzing large data and drawing inferences. Capturing unstructured data and converting them into a structured format are technically challenging problems. They have to be pursued in an enlightened manner. Drawing inferences call for adequate scrutiny of the theory requiring the combined knowledge of the statistician and of the subject expert.
“In this context, it is worth remembering what Albert Camus, the French author and philosopher of the last century, had stated and I quote: ‘The evil in the world comes almost always from ignorance, and goodwill can cause as much damage as ill-will if it is not enlightened’”.
Statistical and allied techniques are depended upon by business for operational and strategic decision making. The corporate sector makes extensive use of Statistics and allied subjects like Mathematics, Economics, Operations Research, Quality Management and Computer Science. Data such as usage of social networking sites, footfalls in large retail stores, hits on websites and usage of credit cards are thoroughly analyzed for widely differing purposes like uncovering hitherto unknown consumer behaviour, assessment of risk, detection of fraudulent transactions and discovering new customer segments. (KNN/ PC)
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