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Decoding the Story Data Jungles Hide

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K R Murali Mohan

K R Murali Mohan
Head – Big Data Initiative, Department of Science and Technology, Government of India

Big Data, in combination with analytics, can produce amazing results that can be utilised for informed decision-making purposes, says K R Murali Mohan, Head – Big Data Initiative, Department of Science and Technology, Government of India, in an interview with Gautam Debroy of Elets News Network (ENN)

What is the importance of the Big Data Initiative division?

This is a new programme launched some six months ago by the Department of Science & Technology (DST). It’s a new and emerging technology and has immense potential in government, public sector undertakings, skill development and entrepreneurship development, cutting across the various spheres of our life.

Going by the definition, Big Data is data whose scale, diversity and complexity require new architecture, techniques, algorithms and analytics to manage it and extract value and hidden knowledge from it. In other words, Big Data is characterised by volume, variety (structured and unstructured data), velocity (high rate of changing), veracity (uncertainty and incompleteness) and value. In the context of Big Data research, so-called analytics is playing a leading role.

Analytics cover a wide range of problems, mainly arising in the context of database, data warehousing and data mining research. Analytics research is intended to develop complex procedures running over large-scale, enormous in-size data repositories with the objective of extracting useful knowledge hidden in such repositories. One of the most significant application scenarios where the need for Big Data arises is, undoubtedly, scientific computing. Here, scientists and researchers produce huge amounts of data per day via experiments (e.g., disciplines like high-energy Physics, Astronomy, Biology, BioMedicine and so on). But, extracting useful knowledge for decision making purposes from these massive, large-scale data repositories is almost impossible for actual Database Management System (DBMS)-inspired analysis tools.

From a methodological point of view, there are also research challenges. A new methodology is required for transforming Big Data stored in heterogeneous and different- in-nature data sources (e.g., legacy systems, web, scientific data repositories, sensor and stream databases, and social networks) into a structured, well-interpretable format for target data analytics. As a consequence, datadriven approaches can replace the traditional hypothesisdriven research in science.

What are the achievements of your division as of now and your road ahead?

The main challenge lies in identification of the problem itself. As of now, we have identified some of the challenges, particularly related to science and technology, though solutions once developed are applicable to any domain or data sets.

Some of the challenges that researchers across the globe as well as in India are facing are related to data deluge pertaining to Astrophysics, Materials Science, Earth and atmospheric observations, Energy, Fundamental Science, Computational Biology, Bio-informatics and Medicine, Engineering and Technology, Geographic Information System (GIS) and Remote Sensing, cognitive science and statistical data. These challenges require development of advanced algorithms, visualisation techniques, data streaming methodologies and analytics. The overall constraints that the community is facing are:

1. IT challenge: Storage and computational power

2. Computer Science: Algorithm design, visualisation, scalability (machine learning, network & graph analysis, streaming of data and text mining), distributed data, architectures, data dimension reduction and implementation

3. Mathematical Science: Statistics, optimisation, uncertainty quantification, model development analysis and systems theory; and

4. Multi-disciplinary approach: Contextual problem solving.

Our roadmap mainly focuses on leveraging our academic strength, connecting to some of the issues our society is facing, and working on how Big Data Analytics (BDA) can play a role in addressing those issues.

big-dataWhat initiatives have you adopted for data digitisation?

Big Data Initiatives Division of the Department of Science and Technology is not directly related to data digitisation. However, it is an issue, particularly when we talk about legacy data. Almost every data-generating organisation has its own plans for data digitisation. We build analytics super structure on that.

What is the importance of ICT in your Department?

Being a scientist and associated with a scientific department, dealing with academicians impels the Department to consider ICT as an integral part of Science and Technology.

What are the major challenges you are facing?

Accuracy, authenticity, data availability and updation are some of the challenges we are facing.

How do you promote implementation of scientific projects across the country?

The Department of Science and Technology promotes science and technology (S&T) in the country and Big Data is a new initiative in the entire S&T setup. We propose to create industry-academia partnership to groom the talent pool in universities and connect them to governmental programmes and feed into policy formulations. We do have plans to develop a strong skill development module for students in BDA, so that their job potential increases. The entrepreneurship development in BDA is another area where we would like to focus. The aim is to equip job seekers well enough to become job creators. A new paradigm, Analytics-as-a- Service (AaaS), is emerging and we are good at it.

Our roadmap mainly focuses on leveraging our academic strength, connecting to some of the issues our society is facing, and working on how Big Data Analytics (BDA) can play a role in addressing those issues

Who are the major beneficiaries of your Big Data Initiative division?

We can’t pinpoint the beneficiaries. It is an enabling ecosystem that we are trying to create. Overall, it has three broad areas. The first one is Research and Development, where academicians and researchers are supported to innovate on development of new visualisation techniques, algorithms, streaming methods and analytical tools, which have high-potential values within the country and across the globe. Second is skill development, where BDA skills and exposure will position our students on a better footing in international and national job market. And, the third area is entrepreneurship development.

Directly or indirectly, the overall beneficiaries involve everyone in the society.

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