XIME Offers a New Specalization in Business Analytics

XIME Offers a New Specialization in Business Analytics

Business Analytics is an inter-disciplinary area encompassing statistics (Quantitative techniques), Information Technology (RDBMS, Data warehousing, data mining, Business Intelligence, Big data, Hadoop etc.) and Business Applications (functional areas of Management viz.; HRM, Finance, Marketing, Production & Operation Management).

There are many analytics tools built incorporating the above by various organizations. Some examples are SPSS, MS Excel (+ extensions), MS Power BI Desktop, Tableau, Hadoop, Hadoop tools like Hive, and programing languages with analytics libraries like Java, R, Python, SAS etc.

Just as the technologies of internet, E-commerce and Cloud have pervaded our everyday lives within such a short span, Business Analytics is going to play a pervasive role in the life of future managers. With data growing very big encompassing traditional databases, Excel based data, unstructured data like Emails, Facebook, videos, photos and chat messages on the web, new tools are required for mangers to analyze these data-spaces and find patterns to derive business intelligence (BI). This BI can be used for competitive advantage in various functional areas. This is already happening.  

We want to prepare our students by offering this Business Analytics specialization stream which consists of 7 elective courses, for job readiness and future readiness.



Sl No

Course Name


Introduction to Database Management (RDBMS,) Data ware-housing, and B.I [Business Intelligence].


Business Analytics using Excel / R / Python  (Multivariate Analysis, Multiple Linear Regression, Logistic Regression, Time Series Analysis, Forecasting, Bayesian Analysis. In depth use of EXCEL. Introduction to R)


Introduction to Big Data and Big Data Analytics, with Tools (Hadoop based tools, MS Power-BI, Tableau etc.,)



Application of BA in
4.1) Finance,
(4.2) HRM,
(4.3) Marketing and
(4.4) Production and Operations

(All these courses will run in parallel)


Adv. Stat Course Multi Regression, Factor Analysis, Principal Component Analysis,  Canonical Correlation, etc., using SAS/SPSS or any other  Statistical tool)


Data Mining: (Using EXCEL /SPSS /SAS /XLMINER/ Power BI or any other D/M package)

Partitioning data, Data Utilities (Sampling), Classification Affinity,

Prediction, Predictive modelling and analysis,  Time Series Analysis,

Data Reduction and Exploration, Charting


Applications of Cloud computing and IOT [Internet of Things] and Overview of AI (Artificial Intelligence).

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