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Information Technology & Data Science:

With everything revolving around big data, artificial intelligence, cloud computing, Internet of Things the future of Information Technology is indeed tremendous. Though last two years were a bit unstable for the industry, however in next 5 years the Indian economy will witness sharp upsurge in Information Technology sector. Usage of emerging technologies with data at the center, Data Science is the prime focus of this sector.

Every IT company is now planning to coincide their services towards Industry 4.0 and hence are blending in latest technologies to offer enhanced services. Usage of emerging technologies with data at the center, Data Science is the prime focus of this sector.

Why Data Science cannot be ignored?
  • Data Science is Everywhere: The potential for Data Scientists across the industries is flourishing. Data Science skills have become imperative for IT/ITES sector in order to be able to compete and improve today’s marketplace.
  • Changing Roles of Data Analysts: With growth in Data Science field there has been an increased overlap among the roles of Data Scientist, Data Analyst and Data Modeler. The thin line is getting thinner and as we go along Data Analyst will transform into Data Scientists.
  • Data is Business Asset: With so much data coming into the industry every second, it is the next business asset. With more companies now making a conscious effort to use data to get actionable insights, IT / ITES sector has to transform and add Data Science offering in their product folio.
  • Right Data and Right Data Sizing: While Data Science is promising and growing at a fast pace, availability of ‘Right Data’ is a perpetual problem. Too much data does not mean right data. It takes away the focus from actionable data and may lead to data paralysis. It is hence important to collect data and correct noise to make a robust analytical model.
  • Right Story Telling: Dealing with complex and intricate models can be intimidating for end users. Hence it is important for Data Science to be able to narrate data stories effectively.
  • Building Data Science Model but Not Solving Problems: The IT/ITES industry has been solving business problems for quite some time now. Data Science team mostly builds Data Science Models that may not necessarily solve real-life problems. Hence business stakeholders tend to lose interest in Data Science.

3Ds of Data Science

While the roles are overlapping for Data Scientist, Data Analyst and Data Modeler, however each one of them brings distinct advantage on the table.
According to Dr. Favio Villanustre, VP Tech & HPCC systems for LexisNexis Risk Solutions:

  • Data Analyst traditionally specialises in data manipulation techniques that require training in query languages and graphical data models.
  • Data Modeler analyses numerical data for correlation and patterns.
  • Data Scientist is a super set of the two above compounded with domain and business knowledge.

The topmost challenge that Data Science and IT industry face together is acute shortage of talent. With only 3 years as average experience in Data Science, Indian IT industry needs upskill their professionals with new skill sets. According to NASSCOM, India needs to upskill at least 50% of their IT professionals to keep them relevant for Industry 4.0.

Advantages of an upskilled Workforce

An upskilled IT professional is an essential part of the right team that is able to take correct calls on Infrastructure (hardware) and Data Science platform (software) implementation for various tasks undertaken at own / client side. This team is ideal as it has right mix of business, statistical and programming knowledge.

How Can SkillUp Technologies help you leverage Data Science?

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