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Home > Blogs > Talent Imperatives for Data Science & Analytics
Manipal Global Academy of Data Science conducted Thought Leadership Series on Digital Transformation – Talent Imperatives for Data Science & Analytics on 10th January, 2017 at Manipal Global Academy of Data Science Campus, Electronic City in Bangalore.
Manipal Global Academy of Data Science invited delegates from Deakin University, Australia as well as Data Science professionals and enthusiasts to the event. The Thought Leadership Series was aimed at discussing talent imperatives for the Data Science and Analytics field. It also served as a great networking event with industry influencers.
There are multiple talent-challenges in Data Science and Analytics field and immediate action is imperative. Following challenges were discussed at the event:
- How to prepare the fresh talent to handle the bent of the industry towards predictive consumer analysis and big data
- How to equip the talent to contribute towards product development and implementation from the start
- Finding out economical and short paths to enable the talent to perform optimally at a certain level
- Delivering more practical exercises and technical know-how to operate sophisticated data tools
- Polishing soft-skills and business domain knowledge
- Teaching the freshers to handle structured and unstructured data
Ms. Vishnupriya Raghavan, Head of Programs, Manipal Global Academy of Information Technology, welcomed all the guests post the High Tea and the brief networking session. She introduced all the members formally while setting the context for Digital Transformation Thought Leadership Series.
The moderator, Mr. Bhaskaran Srinivasan, Academic Director, Manipal Global Education Services, took over after Visnhupriya’s introduction session. He briefly spoke about data science field, its relevance in the present world and how it is still in the “infancy” stage. In addition to that, he emphasized on the importance of education in the domain and set the stage for the discussion. He then invited Dr. Svetha Venkatesh, one of the key note speakers to take over the discussion.
Keynote Speaker #1 – Prof. Dr.Svetha Ventakesh
Prof. Dr.Svetha Venkatesh is an Alfred Deakin Professor in the Faculty of Science, Engineering & Built Environments and Director of the Centre for Pattern Recognition and Data Analytics (PRaDA) at Deakin.
Dr.Svetha Ventakesh kicked-off the event with her presentation on data science and its implications.
“Data is challenging. Data is time-varying and it is sporadic.”- Dr.Svetha Venkatesh
She spoke about what data has done so far and what it can do further. Further, she maintained that data is challenging and it is diverse in nature. She also spoke briefly about the importance of Machine Learning and Predictive Analytics. Further, she highlighted how it is necessary to reformulate the entire problem in the absence of sufficient data. She also spoke about how easy it is to go wrong with the data in hand. So, one has to be extremely careful in handling the data.
Dr.Svetha then steered the course of discussion towards some problems that data cannot solve at this moment.
A very interesting Q&A session followed Dr.Svetha’s presentation.
Keynote Speaker # 2 – Mr. R Nagendra Prasad
Mr. R Nagendra Prasad, CEO at Confluence Consulting Circle, focusing on Product Management and Business Intelligence - Analytics. He is also a faculty at Manipal Global Academy of Data Science
Post the Q&A Session with Dr.Svetha, Mr. R Nagendra Prasad took over the session.
He touched upon various important aspects of “digital transformation” and “discovering the unknowns”. Then he went on to highlight a few problems being faced by the companies in hiring the right data-science-skilled talent. Further, he then explained about CrowdFlower – a data-based company that focuses on understanding the specific talent gaps in data science and analytics area.
“Everyone has data, but what they have to do with that data is something they still have to figure out.”-Mr. R Nagendra Prasad.
Finally, he discussed the pain-points of the data science industry and suggested ways to overcome them.
Q&A Session followed Mr. Prasad’s session.
Important question were discussed, which opened a deeper discussion into the topic of data science and analytics.
One of the most interesting questions that were asked was “What is the right approach to hire the best data-science-talent?”
Mr. Ravi Jain – Vice President and Business Head at a large organization added that a “mix & match” situation is ideal because the data science field does not have any leeway as it has exploded quite rapidly. Therefore, the healthcare companies have tied up with data science companies and councils for pre-analytical training for employees. Continuous learning is the need of the hour as the tools and languages like R, Python and Scala are going to become obsolete soon in the light of increasing data complexity and evolving technological landscape.
“College degrees cannot buy you a lifetime worth of a pay cheque. You have to upgrade yourself periodically.”-Mr. Ravi Jain
Further, he added that short-term business-domain training, applied thinking, tech-hackathons are the best ways to help professionals and students upgrade their skills quickly.
Discussion on IT Industry
Dr. Nishant Chandra, Data Science Leader at AIG Science, spoke specifically about the IT industry.
“In the IT field, our aim is to secure and mature with something that keeps us ahead of the curve within our competitors. Now this is something that is dependent on two factors - the uniqueness of the data, which I produce as a company and what I extract out of it in terms of real insights.” – Dr. Nishant Chandra
Garima Sindal, Senior Manager, Technical Enablement at 7 mentioned that data science is a dynamic space.
“One of the challenges I presently see in the data science industry is that a lot data scientists may get confused about using the various tools available to them. Hence, they take time to research and study the problem and explore various tools to get the solution, which may lead to replication and may not work all the time.” – Ms. Garima Sindal
The moderator, Mr. Bhaskaran Srinivasan, took over and presented his take and analysis on the discussion held and posed a few witty questions in front of the group.
The session was concluded by Mr. Bhaskaran Srinivasan, who revealed the collaboration plans between Manipal Global and Deakin University, Australia to set up a Centre of Excellence focusing on promoting data science and analytics knowledge in India. The partnership will aim at solving the obstacles tying down the industry. They aim to do so by determining the industry-specific anomalies, solving these problems by publishing whitepapers and case studies, to name a few, which will provide an enriching experience to students and help them get in-depth industry knowledge. Hence, Manipal Global Academy of Data Science along with Deakin University, focus on emerging as the leaders in the field by solving the problems crippling the data science industry in India.
“The mass of the population is at the bottom and they do not have the domain competence or business understanding. They want to grow, they have ambitions, but they don’t have access to the right platform to achieve it presently, and this collaboration may prove helpful to them.” - Mr. Bhaskaran Srinivasan
The event was a great success and was extremely interesting for all data science enthusiasts. A lot of important aspects about data science, technology and Manipal Academy of Data Science were discussed. Consequently, great results are expected to come out this partnership between Manipal Global and Deakin University.