Graduate Program Certificate:
Business Analytics

Learn how to decipher data to make more informed business decisions.

How can you best use social media to connect with potential customers? What behaviors fuel purchase decisions? How can you spark a meaningful dialogue with a new generation of customers?

One of the most in-demand skill sets in 21st century business is the ability to uncover new opportunities, insights, and strategies through the analysis of business data. The Business Analytics Concentration takes a deep dive into the analytic mindset, giving you an in-depth look at the quantitative methods and cutting-edge analytics software tools used for strategic, data-driven decision-making, including:

An MBA with a business analytics background is an in-demand asset for nearly every industry and economic sector.

Careers in Business Analytics

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Data Scientist
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Data Engineer
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Analytics Manager
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Database Administrator
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Alternative courses can be considered in certain circumstances. Permission of the Program Director or Associate Dean for Graduate Programs is required. Contact your graduate academic advisor.

This course provides an overview of business analytics, emphasizing how firms implement data-driven decision making. Students will learn an array of statistical concepts and different analytics methodologies, use spreadsheet modeling and learn through a mix of lectures, cases, practice problems and class discussions. The course will also provide opportunities to apply these concepts hands-on using a language such as “R.” An important goal of the course is to make students understand and implement fact-based decision making and enable them to become comfortable in gathering and analyzing data in order to make managerial decisions. Topics include exploratory data analysis, sampling, hypothesis testing, regression modeling, experimental design, analysis of variance, text mining, web analytics, and social media analytics. Case studies and assignments will introduce students to various contemporary business applications and innovative use of these ideas.
Prerequisite: Quantitative Skills 53:135:502, unless waived.

This course focuses on the design and management of the data resources of an organization and the extraction of business intelligence from the data for managerial decision making. The basic concepts and techniques of data management and mining data will be examined with real-world examples and cases to place these techniques in proper context. The Data Management module covers the fundamentals of robust data models, management of data resources, and the retrieval of data using SQL/NoSQL. The Business Intelligence module focuses on the concepts and applications of various data mining models such as classification and clustering, and provides an overview of machine learning. The course delivers adequate technical detail with hands-on training, while emphasizing potential interpretation, organizational, and implementation issues relevant to managers. Topics include conceptual data modeling, database management, structured query language, business intelligence, classification, clustering, and introduction to machine learning. Prerequisite: Business Analytics 53:716:502.

The course provides students with an in-depth introduction to the Hadoop ecosystem, which is an environment used by companies to store and manipulate “Big Data” of a size and scale that cannot be fit into traditional databases. Students will be exposed to tools, such as Sqoop, Pig, and Hive, for ETL (extract-transform-load) operations within Hadoop. The course also provides exposure to state of the art data mining algorithms for clustering, classifying, and collaborative filtering (a technique used by businesses to recommend products to customers). Participants will build machine learning applications with Apache Spark. In the second half of the course, students will learn information design, specifically tactics for visualizing Big Data that can consist of temporal, spatial, topical, or network relationships among entities.

Prerequisite: Data Management & Business Intelligence 53:623:517. Also, students should have familiarity with the Python programming language before taking this course.

Electives include the following courses, among others:

   Financial Data Analytics 

   Data Analytics and Visualization 

   Supply Chain Analytics   

   Database Marketing 

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BLDP Shadowing Days Application

After being notified of a match, students are responsible for providing personal information to the matched executive (e.g., current resume and cover letter with information on career ambitions). The information on this application is for internal use only, for us to match you as well as possible with and executive from among our alumni database.

BLDP Application

The Fall 2021 Application is now open! 

Priority will be given to applications received by Friday, April 2, 2021. Applications are accepted until all seats are filled. Space is limited, so apply early!

The seminar application process is our gateway for entry into the program. Upon acceptance into BLDP, students will be emailed their acceptance letter plus a special permission number allowing registration for the BLDP seminar.


Seminar applications are solicited each semester and require the following:

  1. Completed application form (at the bottom of this page),
  2. Personal essay
  3. Two (2) letters of recommendation (one academic; one other)

Rutgers-Camden students are invited to apply to apply for enrollment in the BLDP seminar. All applicants are expected to meet both of the following selection criteria:  (1) have sophomore standing or above and (2) have an overall GPA of 3.0 or above. First-semester transfer students will be evaluated based on their GPA earned at Rutgers. Students who fail to meet these admission criteria may still be allowed to apply for (and possibly enroll in) the BLDP seminar, but they will be evaluated on a case-by-case basis.

The director balances evaluations to make final decisions on people accepted for the seminar (up to a maximum of 15-20 each semester).

Students who are admitted to the BDLP are required to adopt the BLDP Code of Conduct. A signed contract is required from each student.

Students may count activities toward “leadership units” that were initiated prior to taking a seminar, as long as those activities occured primarily during their enrollment in their academic program.

Application for Admission to BLDP Seminar

Applications for the BLDP Seminar will be ongoing until class is filled.

  • * Indicates a required field.

  • Contact Information

  • Academic Information

  • Please enter a number from 0 to 500.
  • Transfer students only.
  • Employment Information

  • List relevant employment history

  • EmployerPositionDates of Employment 
  • School Leadership Information

  • Provide evidence of leadership initiative while enrolled in school by listing all school-based organizations and activities in which you have held a leadership role while a student.

  • OrganizationRoleDates 
  • Community Leadership Information

  • Provide a list of community or volunteer activities in which you engaged in a leadership role.

  • OrganizationRoleDates of Activity 
  • Essay

  • Please write a short essay between 150 to 350 words, in which you discuss the reasons why your application should be considered for the Business Leader Development Program, including what you hope to gain from the program and what you can contribute.

  • Additional Submission Instructions

  • For your application to be complete, this form and TWO REFERENCE LETTERS must be on file in the Student Experience Center. Ideally, you should receive one letter from an academic source (e.g., a former or current instructor), and one from a business source (e.g., a former employer - even if for a part-time or volunteer position). Your letter writers should be mail them directly to: Dan Rosenthal, Student Experience Officer, Rutgers University, School of Business, 227 Penn Street, Camden, NJ 08102 or email the letters to

    Please only submit one application. If you experience any technical problems or need to submit the application again, please contact

    Thank you.

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