Dr. Lalit Sharma is an academician, trainer and consultant with 21-plus years of rich experience in the domain of Business Analytics and Information Systems. Presently, he is acting as Area Chair-Business Analytics in Jaipuria School of Business. He has done his PhD in Data Mining. He has been actively involved in curriculum development/iteration, Technology infusion, NAAC and NBA accreditation documentation and instructional design processes. He has been associated with Internal Quality Assurance (IQAC) by analyzing effectiveness of teaching material and methodology.
Data is raw material that can be forged into powerful solutions for furthering an organization’s objectives. Analytics professionals develop the systems to organize and structure quantitative information, identify valuable insights and create reports and visualizations to convey their findings. These steps lay the foundation for actionable business intelligence, helping leaders to understand their organization’s position in the marketplace and make informed decisions about how to stay ahead of their competition. Companies in almost every industry now collect vast amounts of data about their customers, competition and supply chains. But gathering information is relatively simple. Discovering the full value of data analytics in business is a constant challenge.
Most organizations today have already built some of that foundation—they’ve begun collecting data and running descriptive analytics tools like dashboards. What many companies still need, however, are the supporting elements to conduct predictive and prescriptive analytics processes and successfully take action. Gartner predicted that through 2022, only 20% of analytics initiatives will deliver on business objectives. What’s happening to the other 80%?
It’s easy to fall into a technology-first approach when thinking about analytics, but the most common causes of failed analytics projects are not the wrong tools or a lack of technical proficiency. In fact, many of these issues are business problems:
- Asking the wrong questions
- Failing to define a clear purpose for collecting data
- Selecting the wrong uses for analytical methods
- Lack of supporting business culture
It takes technical expertise and business acumen to establish the conditions for analytics to thrive. Leaders must know which technologies to use, when to deploy them and how to optimize the outcomes.
While there are plenty of graduate schools that offer master’s degrees in analytics, choosing the right educational path could make a big difference in your career. A business school big data analytics curriculum teaches the concepts, tools and techniques to guide an organization’s growth and transformation — going well beyond basic data analysis and statistics. If you’re ready to take the lead in making quantitative information really count, a Master of Science in Business Analytics from an internationally renowned school of business provides advantages that you won’t find in other programs.
There is a huge demand for graduates with an interest in data science and business analytics. This is how these skills could help you advance your career.
- Businesses across the globe are demanding these skills
The first, and the most obvious, reason why these two skills can make you so employable after graduating is that they are so in demand by employers. Businesses across the world are trying to get to grips with big data, and need people with specific skills to help them make sense of the vast amounts of information to which they now have access.
Data analysts are extremely valuable and sought-after people that every business wants to work with. So, if you have learnt these skills during your degree program, you’ll have the pick of companies to work for – it also means you could command a much higher salary.
- You’ll have important problem-solving skills that employers’ value
With data analytics, you’re presented with endless amounts of information and it’s up to you to figure out a solution based on what you’re seeing. You’ll be problem solving a lot when you enter any company, and potential consequences could be on a much larger scale than what you’ve been used to during your studies.
Businesses don’t want to make mistakes, so they want people on their team with excellent problem-solving skills – something that every data analyst has.
- You can identify trends and turn them into goals
When you spend your time examining data, you’ll quickly find it easy to identify trends and similarities. With this information, you’ll be able to recommend and advise on the best course of action to improve your company’s performance.
Turning trends into goals takes skills, but, when done correctly, it can engage customers, boost profitability and ensure long-term success.
- You’ll be able to identify and refine your company’s target audience
A company can never succeed if they aren’t targeting the right customers: however, many businesses don’t know where to start when it comes to identifying these groups. Data scientists will be able to take existing data – which might not be useful alone – and manipulate it to generate insights that your company can use to discover their perfect customers and engage effectively with them.
You’ll be able to precisely identify the groups of people that will be most interested in your business. This takes the risk out of your next marketing campaign and allows different departments to tailor their offerings accordingly to suit your customer base.