Learn to make better business decisions backed by data insights
By Michelle Chin
July 7, 2019
In today’s business climate, it may take more than just gut instinct to survive the tough competition. The challenge is to improve your strategy to stand out from the rest.
Better business outcomes can be achieved from tapping insights derived from understanding and mining data, says Dr Rita Chakravarti, programme head of the Master of Technology in Enterprise Business Analytics (MTech EBAC) programme at the National University of Singapore’s Institute of Systems Science (NUS-ISS). She shares her views on how this can be achieved.
It is a field that enables businesspeople to benefit from diagnostic, predictive and prescriptive analytics to have more efficient planning, inventory management, better market segmentation, competitive pricing and more.
It includes quantitative disciplines such as statistics, operations research (a discipline on the application of advanced analytical methods for decision-making), computer science and machine learning.
Additional applications are forecasting demand, planning supply chain, reaching out to customers in a more targeted way, detecting fraud, predicting credit worthiness and more.
Although business analytics methodologies have been used for more than 50 years, the growth was limited by high cost of data collection and storage, insufficient computing power and reliance on expensive proprietary software.
However, in the last ten years, several factor propelled the field into exponential growth:
i) Technological progress enables superfast computing. Terabytes or more of data can be processed in a reasonable amount of time;
ii) Sharp decrease in the cost of data storage;
iii) Availability of reliable open source software like R and Python for building predictive models; and
iv) Phenomenal advances in the fields of statistics, operations research, computer science and machine learning.
These factors significantly lowered the cost of solving business problems through analytics and led to widespread adoption of such technologies.
This trend is accelerating and dramatic growth in this area is certain. But what’s hindering even faster growth is the shortage of trained professionals.
It can be completed full-time in one year or part-time in two years, and is ideal for those who like working with numbers and have significant work experience (a minimum of two years) in quantitative fields. Some coding experience will be helpful.
Graduates will be trained in data handling, problem formulation, statistical and machine learning algorithm development and solution implementation. They will also learn about customer management, big data handling, natural language processing, as well as special kinds of modelling and forecasting techniques that are required in niche areas.
Learn more about the NUS-ISS MTech EBAC at the information session.
Date: July 13, 2019 (Saturday)
Time: 3.30pm to 5pm
Venue: National Library Building, Level 3 (Function Room 2)
Scan the QR code below for more information.