Why Machine Learning is Important for Business Analytics? - Great Learning

Why Machine Learning is Important for Business Analytics?

A Business Analysts role is multifaceted. Right from formulating a client’s business problem to finding insights to communicating those in the most comprehensible and convincing way are all under a business analyst’s purview. During the entire lifecycle of a data analysis project, a business analyst actively works with various teams for fruition. They will collaborate with data scientists to understand if they will need to trade accuracy for practical implementation. They will collaborate with the clients to prove how their recommendations and insights are derived from data. With this overlap in roles on all ends, a business analyst needs to expand his capabilities to be effective. That’s why we introduced the Machine Learning module in our PGP-BABI program to ensure our students continue to have an edge in the analytics domain. Machine Learning is an integral tool in a Business Analyst’s arsenal because of the following:

Complexity of Data – The rate at which data is being generated from different sources is going up and working on complex unstructured data is becoming inevitable. There are two aspects to such data. It can be complex either because it has been gathered from different sources and creating models can be hard, or it is complex because of the nature of data generated such as in handwriting analysis or NLP. Not everything can be directly put in rows and columns. Data collection, data cleansing, and data mining are fast becoming more complex than just importing data from a primary or secondary source to analyze. Classic examples would be Twitter data for sentiment analysis or satellite images for crop coloring to predict yield. This is why we introduced Python as an optional module in the program for those who would want to walk that extra mile to learn it.

pgp business analytics (pgp-babi) great learning

Upcoming Areas of Study – One of the greatest gifts of analytics is our ability to apply it to a plethora of problems across industries and domains. And so it is imperative for a competent business analyst to be able to work without constraints. Our machine learning module helps them work on several of these fields like audio/video analysis, handwriting analysis, sentiment analysis, image analysis, natural language processing (NLP) that are still catching up and a business analysts’ ability to work with a diversity of data and apply relevant tools and techniques will become the parameters for career success and competence. While these fields will require domain expertise, without understanding the depth to which data will need to be explored can make or break a project.

Machine Learning Tools and Techniques – A business analyst will not only be using structured but a combination of structured and unstructured data to draw insights. Without basic knowledge of machine learning concepts like supervised and unsupervised learning, SMOTE, oversampling and undersampling, a business analyst will be at sea while dealing with complex data. Case studies, quizzes, and assignments done in the machine learning module during the program help our candidates develop a deep understanding of cases when they should or should not be using different machine learning techniques.

pgp business analytics (pgp-babi) great learning

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