MBAs are sought after for their ability to think critically, deal with ambiguity and solve the complex problems. But due to the growing volume and velocity of data, today MBAs are expected to make quicker, and more accurate data-driven decisions to grow a business- which is only possible with knowledge of ANALYTICS.
Business Analytics (BA) and its related terms such as Business Intelligence, Big Data, Data Mining, Data Science, etc. have become a powerful tool for growth in the 21st Century. Edupritine predicts that by 2018, there will be a 50% gap in the supply of data scientists versus demand. Which clearly means that the demand for data scientists and Business Analysts is increasing at a breakneck speed.
The Business Analytics Course is open to all MIT masters-level programs (e.g., MBA, EMBA, MFin, Sloan Fellows, LGO, SCM, SDM, TPP, etc.). Students are allowed to pursue more than one Course (such as Healthcare or Sustainability). Students are allowed a shared elective and a shared action learning project when pursuing more than one Course.
Business Analytics vs. Data Scientist
The role of a Business Analytics involves researching and extracting valuable information from data sources to explain business performance (present and future). A Business Analytics also determines the right approach to improve the business.
Business Analytics come with domain expertise but limited statistical abilities. This gap is filled by Data Scientists who are advanced statisticians.
How do you multiply the role of the data scientist without the workforce to support it? As organizations are asked to do more with the same, they’ll rely increasingly on data to root out efficiency gaps and provide opportunities for workflow automation. And that goes for the data scientist and his workload as well. Automation will empower the data scientist to empower everyone else at the company, and they’ll need the help of software. Merely throwing more data scientists at the problem of data management won’t solve it.
A Data Scientist develops and deploys algorithms using statistical programming that support the Business Analytics plans. A Data Scientist automates the Data Analyst’s plans and models to help the business enhance output and performance.
Why build a career in Business Analytics?
Analytics, as an industry is set for exponential growth. With more and more data being available in digital form, need for smarter, faster, data based decisions is only going to increase. Consider following facts to substantiate what I am saying:
According to Harvard Business Review (October 2012 edition), job of a data scientist is the sexiest job of 21st century.
According to the Edu pristine (In a May 2011 report): “By 2018, the India alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”
Imagine what would be the number across the globe…
There has been extensive popular interest in BA over the past few years, including popular business press books like Competing on Analytics and Predictive Analytics. This reflects the significant business interest in translating analytics into business advantage. Employment forecasts predict a huge growth for managers that understand analytics to lead big data initiatives in the U.S. over the next decade. Our graduates have accepted jobs from companies such as Microsoft, Amazon, Johnson & Johnson and Bank of America, and top consulting firms like Deloitte, IBM and McKinsey, that are leading efforts to bring analytics to the forefront in business.
With experts predicting that 40 zettabytes of data will be in existence by 2020, careers hinging on analytics will only shoot through the roof. Shortage of skilled professionals in a world which is increasingly turning to data for decision making has also led to the huge demand for Business Analytics and Data Scientists in start-ups as well as well-established companies.