Analytics & Data Science

Every time a customer interacts with a computerized system, whether at a Grocery Store, Online Store, or Social Media site, data is created and stored in a data solution system. Tools then convert this data into metrics (known as analytics) that assess consumer behavior.

Analytic professionals interpret analytical data and utilize statistics, predictive modeling, and managerial strategies to drive business decisions. Analytics are used in nearly every industry:

  • Marketing companies use analytics to measure and analyze performance of different initiatives
  • Financial firms use analytics to analyze investments and forecast future scenarios
  • Charter schools use analytical data to inform teaching practices
  • Major movie studios use analytics to project ticket sales

Behavior analytics, an emerging subfield, deals with the analysis of eCommerce platforms, mobile applications, and websites to gain insights into their customer base. Behavioral analytics seek to assess what consumers do, who they are, and how their behavior might impact future behavior.

Related to the field of Analytics is Data Science. Data scientists rely on data sources, statistics, and analytics, but focus more on the application and modeling of data. Data Science is an interdisciplinary field that uses scientific processes and systems to extract knowledge and insights from data in various forms. Data Scientists borrows techniques and strategies from many fields, including computer science, mathematics, and information sciences.

Increased use of applied analytics and data science in all industries has created more opportunities for stat-savvy liberal-arts graduates.


Get Experience

Given the ever-evolving nature of the field, students interested in breaking into the fields of Business Analytics and Data Science should get experience before attending graduate school. With that being said, there are a number of really good graduate programs in the field for professionals with relevant experience.

Think about MBA and MS graduate programs

Broadly speaking, programs in Data Analytics and Data Sciences can be broken up into Masters of Business Administration (MBA) programs and Masters of Science (MS) programs.

MBA Programs are geared more towards professionals interested in making decisions about data, whereas MS programs focus more on the technical applications. Obviously, one's background in either Business or Science (e.g., computer science or engineering), will make them a stronger candidate for their respective graduate program. Increasingly, programs offer interdisciplinary options combining aspects of both Business and Science.

Top 25 Graduate Programs in Business Analytics + 23 Great Programs in Data Science

Dive into extracurricular coursework

Although specific undergraduate coursework in analytics and data science is not always available to liberal arts students, there are a number of free and paid courses that provide students with basics in the field. Here are a few:

Explore Careers

Given that the field is quickly growing, there are a number of places where students with an interest in Business Analytics and/or Data Science can land from traditional Fortune 500 companies to tiny startups. These include, but are not limited to, the following industries and subfields:

  • marketing
  • consumer products
  • finance
  • consulting
  • healthcare,
  • accounting
  • insurance
  • telecommunications
  • pharmaceuticals
  • biotech
  • and all types of technology companies (including companies specifically focused on Analytics)
Typical titles for Business Analytics include Business Analyst, Data Analyst, Marketing Analyst, Data Consultant, Business Analytics Professional, and Predictive Analytics professional.

Typical titles for the field include: Data Engineer, Data Analyst, Data Scientist, and Machine Learning Specialist or Engineer.

Well known employers of Business Analytics professionals and Data Scientists include:

  • Bain & Company
  • Google
  • McKinsey
  • Splunk
  • Cloudera
  • Hewlett-Packard
  • Microsoft
  • Sumo Logic
  • Dell
  • Hortonworks
  • Oracle
  • Tabluea Software
  • Domo
  • IBM
  • Salesforce
  • Trifacta
  • Gainsight
  • Informatic
  • Snap Logic


Let's start with the business interview.

Preparing for interviews in the Business Analytics and Data Science fields can be tricky. Employers in the field typically ask a combination of traditional, behavioral, technical, and problem-solving questions. Though you typically won't be expected to prepare for a formal CASE interview, doing a CASE practice interview can help prepare you to answer scenario-based questions you're likely to encounter.

Here are a few suggestions to effectively prepare:

  1. Research everything you can about the target organization and interviewers
  2. Craft a compelling, but true, reason for why you want the job
  3. Prepare 6-8 examples of relevant past accomplishments
  4. Use Glassdoor and your alumni network to get insights into the interview process and potential questions. Question types and interview strategies vary widely in the field, and tend to be organization/opportunity specific.
  5. Prepare at least 3-5 questions to ask the interview. Check out article here for tips for asking good questions.

Interviewing Resources

Report an issue - Last updated: 03/15/2023