Future Opportunities in Technology

Dr.Hari Krishna Maram Chairman Vision Digital India Interview on Future Opportunities in Technology

Exclusive Interview on Future Opportunities in Technology by Dr.Hari Krishna Maram Chairman Vision Digital India.

 

What is Data Science, Business Analytics and Big Data?

 

Data has got tremendous potential to serve the business. In last few years the speed and volume of data has been generated is phenomenal. Now organisations are data rich but are unable to handle these data properly and thus not able to get proper insight from the data. On the other hand, some of the companies like google can recommend you advertisement based on searches you made online, banks are able to predict fraud in credit card transaction, Online portals are able to recommend you product based on your purchase history, Apps in your mobile phone can forecast rain etc. It is possible because they are using data science and machine learning.

Data Science consists of three main are:, Statistics, Computer tools and Domain knowledge. The data can be stored in structured or unstructured (Big Data), one can apply concepts of mathematical modeling using tools available to solve problems related to business, government, social issues etc. Power of computational power make it possible to work with huge volume of data easily, which was otherwise manually close to impossible.

Most of the decisions have significant economic impact on business. To make decision mangers are required to depend on data. Business Analytics or Analytics is use of data, Statistics, Quantitative methods and information technology and mathematical or computer-based models to help the mangers to gain insights so that they can take better decisions based on insights gained. In other word, the process of transforming data into meaningful insight using statistical models and computational power and tools to address Business problems is Analytics. Here we concentrate is structured data generally.

Big data is collection of unstructured data stored in various platforms such as facebook, twitter, youtube etc. There are different technologies now a days available such as Hadoop, spark etc. to deal with such a massive volume of data. Big Data has 4 dimensions – 4Vs i.e. Volume, Variety, Velocity and Veracity. Earlier this job was done by IT professionals by managing warehouse. Big data helps the data scientist to for further analysis of data by providing basic infrastructure.

 

What is the current scenario of Data Science/Big Data/Business Analytics in the Indian context? How are these moulding themselves as a lucrative career option?

 

According to a recent India Jobs study, data science is the fastest-growing field in India. As every company turns into a technology company, organisations in industries such as manufacturing, healthcare, retail, telecom, healthcare, oil and gas, manufacturing, airline, e-commerce, etc are all trying to grow as data-driven organisations. They are looking to strengthen their data teams. India is emerging as one of the world’s largest data science capitals. India has a large number of people who have the knowledge of coding. That’s how it’s become quite a lucrative career in India. Every industry is hiring Data Scientist. In every functional area, data scientists are required.

 

What are the possible gateways to begin a career in Data Science/Big Data/Business Analytics fields?

 

To begin with a career in Data Science/Big Data/Business Analytics one is required to learn and apply the concepts either using any of the MOOCS such as edX, Coursera, Udemy etc. or one can join structured PGDM programme on Data Science offered by various good Institutions. Now a days industry are putting more emphasis on what you can do for me rather than what you know? Project is one of the major criteria to evaluate the students.

 

Who can pursuing a career in the field of data? 

 

In this field one must study a new technology, algorithm almost daily. So, anybody who has interest to learn, is hardworking and even if they don’t know coding but has willingness to learn and gain proficiency can start career in this field. However someone with good background of maths and coding  adds on advantage.  There is myth that this field is only for engineers, but in real life non-engineers are also doing very well in this field.

 

What are the possible challenges in this career field?

 

The demand for data science has increased globally drastically for those who are equipped with domain knowledge and applied skills such as Mathematics, Statistics, Machine Learning, Deep Learning, NLP and R, Python, SQL, Visulaizations tools such as Cognos, Tableau, Watson, Power BI, Click view and Big Data such as Hadoop, Spark.

It’s little time consuming and little difficult to acquire these skills set. One can learn technology in the class room, but domain knowledge comes with real world experience. In our course we have tried to incorporate various case studies and projects to make students understand domain knowledge as well.

The demand for data scientists are growing, but Indian academia and Industry are not in position to fulfil the requirement. Even there are not enough teaching faculties are available to train in this domain. Another major challenge is poor knowledge of maths and statistics and due to this people struggle to understand the concepts and trying to do coding in machine learning, and hence not able to understand what they are doing, why they are doing?

 

How much rewarding are the professions in these specialised sectors? What is the growth graph in these career fields for next five years?

 

Application of Machine Learning, Artificial Learning, Deep Learning and data science has been increased drastically and almost all industry in India and in world started using it. Some of the Industries where these technologies are used are Telecom, IT, Insurance, Medical Science, Pharma, Oil and gas, Manufacturing, Automobiles, banking, retails, media, e-commerce, government, etc. But major challenge is there are not enough skilled data scientists are available. Compared to market average it takes five more days to hire a data scientists or Analyst. According to one of the report by 2020 there will be 28% more demand for the data scientist. Companies are willing to pay premium to data scientist. A data Scientist with 10 years of experience in Stats and maths can get minimum 1 crore Rs. Per annum.

 

How Vision Digital India is contributing to the field of Data Science? Are you also offering any Courses in this area? If yes than how it is different from other players?

 

We do understand importance of area of Data Science, and our mission is to make people equipped with the contemporary technology and tools. Keeping it in mind we have been giving training in the course like digital marketing (Google Certification), IBM Cognos Insight and IBM Watson Analytics (in Association with IBM). After doing lots of study and research we developed course in data science which we are going to cover in 200 hours. The course has been designed in such a way that engineering, management or any other students or executives will be in position to understand the concepts and will be able to learn the subject by putting efforts.

The main tools of our course are Excel and Modeling with Excel, Tableau, IBM Cognos, IBM Watson R, Python and Statistics. Students are also going to learn Machine Learning using R and Python.

This course is well suited for those people, who would like to make their career in Data Science and Machine Learning. Our fee is less than Rs. 1 Lakh. Students will be getting $75 worth learning credits from Amazon Web Services. They will also be able to access platform of Xcelerator, where by earning required credits they will be able to get internship/placement.

They will be getting certificate from IBM for Analytics for all. 

In this way it is sure going to help people acquire required skill sets and can get good career opportunities in their life.

 

 – Dr.Hari Krishna Maram

Leave a Reply

Your email address will not be published. Required fields are marked *

*