Career after M.Tech in Data Analytics
Career after M.Tech in Data Analytics has excellent opportunities at least for the next decade, for anyone who is interested and passionate in the analysis of data. As per the prediction by CISCO, the global IP traffic will reach two zettabytes where one zettabyte is equal to one billion terabytes.
What is the source of data? It is not just the data that is being posted in the internet by the billions of people. It is also from the communication devices used by the people all over the world to get connected with each other. As the number of devices increase, there is high potential of data growth. Among these, the consumer devices play the vital role in the growth of data. Here comes the potential and power of a career in data science irrespective of the discipline you pursue your undergrad. Technologies like AI, IoT adds the power to data analytics, data science and machine learning with the growth of data. The importance of data analytics lies in the tools used to analyse the unstructured data that is collected through various sources. So far, the scientists were handling only structured data sets with the help of relational databases.
M.Tech in Data Analytics
An important difference between Data Science and Computer Science is that data science heavily uses the more continuous aspects of mathematics together with considerable statistics. It is different from statistics in so far as there is an intense concentration on efficient algorithms to handle very large data sets, in some cases streamed data, and their realisation via different architectures and platforms.
In this current technological era, all the activities of any organization is digitized. All the data is described digitally and becomes the life blood for any organisation. A career in M.Tech Data Analytics will certainly give you 100% job security for the next 10 years. Data Analytics, Data Science, Machine Learning, Artificial Intelligence go hand in hand and is being applied in all the domains now. Let it be health care, banks, insurance sector, information technology, aviation industry – all are covered under data analytics.
Data science is concerned with the acquisition, storage, retrieval, processing and finally the conversion of data into knowledge where the quantum of data is very large. Two current disciplines that have strong overlap with data science are computer science and statistics.
A career after M.Tech in Data Analytics can get you a job in any industry of your choice. The only requirement to pursue M.Tech in Data Analytics is to have a passion to learn some core computer science courses such as Data Structures, Fundamental Mathematics, Algorithms, etc. If you intend to do just the analytics, not coding, then these are not ‘very important’. Efficiency, accuracy are the keys to have a good analysis for any given set of data.
All these said, one of the major challenges in this domain is a rising skill gap. Skill is an important aspect as far as the data science and analytics is concerned. Since data analytics and management is comparatively an older stream within the tech world compared to Artificial Intelligence. The requirements of now and the future will rest more on the analytics in any domain. The burning question is how we can intelligently use huge volumes of data for business transformation including incremental revenues. Every organisation needs to improve their business by offering better services in the competitive market. Cutting of costs, improved decision making and targeted marketing are very important and essential. Therefore, most of the skill gap around data management now lies on Real-Time Analytics, Predictive Modelling, Data Security. Distributed Storage and Data Mining
Job & career after M.Tech in Data Analytics
If you are looking for a career after M.Tech in Data Analytics, a typical data-centric workforce, framework and skill requirement would include the following:
Data interpretation and visualisation with job roles such as Data Analytics and Business Intelligence. In this domain. the skill requirement will be focused on learning the tools for data analytics and warehousing such as Netezza. MicroStrategy. SAS and Tableau.
Data Management and Processing with job roles such as database administration, development, data integration and data lifecycle management. IT professionals in this domain need to work and gain skills on database software and platforms such as Microsoft, Oracle, Cloudera and Hadoop. Data Infrastructure. which is the system behind data management, includes job roles in data storage, data centre management. business continuity and data security.
The jobs titles will change from data scientists to data detectives, tester to ethical sourcing engineer, designers to Al Manager, planners to Cyber City Scientist and others. These jobs will need people trained and specialised for the particular technology.
In the past 10-15 years itself, job sectors have moved away from mere coding to building large scale systems, database systems have stirred to big databases and large programmes running on computers are being used on on smaller devices as ‘apps’. In the next 10-15 years, we may not even need devices to store and run applications. Every facility at home or office will run all applications from cloud or fog.
The top three career options in this sector would be Artificial Intelligence Scientists, Digital Finance Advisors, and Data Detectives. To become an expert in these areas. one has to learn courses like Machine Intelligence. Deep Vision, Data Science, Sensor Technologies and Smart Networks.
Almost all the top institutions in the country offer M.Tech in Data Analytics though it is not directly mentioned in specialisation.