Business Data Analytics Degrees

A degree in Data Analytics will prepare you to help businesses make smart marketing decisions. You will play a crucial role in the success of any business that you join.

Education & Training

Schools with Data Analytics Programs

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What Do You Learn?

A curriculum in data analytics might look something like this:

General Education Requirements

  • Cornerstone Math (CMAT)
    • Introduction to Quantitative Analysis
  • Exploration: Scientific and Mathematical Fluencies (ESMF)
    • Precalculus
    • Applied Statistics for STEM
  • Additional General Education Courses
    • Introduction to Physical and Human Geography
    • Influential Communication through Visual Design and Storytelling
    • Introduction to Systems Thinking
    • Introduction to Communication: Connecting with Others
    • Composition: Writing with a Strategy
    • American Politics and the US Constitution
    • Applied Probability and Statistics
    • Applied Algebra
    • Natural Science Lab
    • Critical Thinking: Reason and Evidence
    • Design Thinking for Business
    • Health, Fitness, and Wellness
    • Discrete Math: Logic
    • Ethics in Technology
    • Discrete Math: Functions and Relations

Major Core Courses

  • Core Data Analytics Courses
    • Introduction to Structured Database Environments
    • Introduction to Scripting
    • Calculus I: Single-Variable Calculus
    • Applied Statistics II for STEM
  • Specialized Data Analytics Courses
    • Role of Data Analysis in Organizations
    • Gathering Requirements and Collecting Data
    • Data Policy and Decision Making
    • Emerging Technologies and Big Data
    • Data Validation: Getting the Right Data
    • Data Validation: Quality and Cleaning
    • Data Analysis Techniques
    • Leveraging Data Analysis for Organizational Results
    • Applied Data Analysis
    • Communication in STEM Professions

Technical and Practical Skills

  • Excel and Data Analysis
    • Excel Data Analysis
    • Analyzing and Visualizing Data with Power BI
  • Database Management
    • Database Management
    • Data Analytics Technologies
  • Data Integration and Management
    • Applied Data Integration and Manipulation
    • Data Analytics Management
    • Applied Data Reporting
  • Machine Learning
    • Practical Machine Learning

Data Management and Analytics Technical Certificate (Optional)

  • Database Fundamentals
    • Introduction to Database and MySQL
    • SQL Fundamentals
    • Statistics or Foundations of Mathematical Reasoning
  • Data Analysis and Visualization
    • Excel Data Analysis
    • Analyzing and Visualizing Data with Power BI
    • Data+

Additional Skills and Knowledge Areas

  • Scripting and Programming
    • Introduction to Programming in Python
    • Scripting and Programming – Foundations
  • Network and Security
    • Network and Security – Foundations
    • Full Stack Engineering
    • Version Control
  • Computer Science
    • Data Structures and Algorithms I
    • Web Development Foundations
  • Information Technology Management
    • Cloud Foundations
  • Advanced Data Management
    • Data Management – Foundations
    • Data Management – Applications
  • Data Science and Analytics
    • Introduction to Data Science
    • Data Analysis with R
    • Machine Learning
    • Machine Learning DevOps
    • Big Data Foundations
    • Data Wrangling
    • Data Visualization
  • Business Management
    • Change Management
    • Business of IT – Project Management
    • IT Leadership Foundations
  • Business Core
    • Fundamentals of Spreadsheets and Data Presentations


Below are some relevant certs that your degree may qualify you for.


CompTIA Data+ is an early-career certification aimed at professionals involved in data-driven business decision-making. This certification equips individuals with the skills to collect, clean, and analyze data from various sources, ensuring accurate and meaningful insights. By enhancing capabilities in data mining, statistical analysis, and data visualization, certified professionals can effectively communicate their findings and drive better business decisions. CompTIA Data+ also emphasizes data governance, quality, and control, making certified individuals valuable assets in any organization. With this certification, data analysts can differentiate themselves, improve data literacy, and become more employable and upwardly mobile.


AWS offers comprehensive training in data analytics through on-demand courses designed by AWS experts, starting with the AWS Data Analytics Learning Plan for beginners. This plan guides you through a structured curriculum to learn data collection, processing, and visualization using AWS services. For more advanced learning, the AWS Ramp-Up Guide provides a wide range of resources, including digital courses, blogs, and whitepapers, to further develop your data analytics skills.


Google’s Data Analytics Certificates offer remote, online learning to help you gain in-demand skills in data analytics, including R programming, SQL, Python, and Tableau. This program provides hands-on training and connects you with over 150 employers, making it easier to start or advance your career in data analytics. With no prior experience required, you’ll learn to prepare, process, and analyze data, and create visualizations to support business decisions, qualifying for roles like data analyst, operations analyst, and business systems analyst.


The Microsoft Certified: Power BI Data Analyst Associate certification validates proficiency in modeling, visualizing, and analyzing data using Microsoft Power BI, aligning with business and technical requirements. Candidates should deliver actionable insights, enable self-service analytics, and collaborate with stakeholders to transform, model, and visualize data while ensuring data security. This intermediate-level certification, which needs renewal every 12 months, also prepares candidates with specific courses and practice assessments and offers potential ACE college credit upon passing the exam.


To become a SAS® Certified Statistical Business Analyst, you must master skills such as analysis of variance, linear and logistic regression, preparing inputs for predictive models, and measuring model performance. The certification exam covers these areas, with specified weightings for each topic, and resources like training courses, tutorials, and practice exams are available to help you prepare. Additionally, SAS offers academic discounts on certification exams and learning materials for students, educators, and independent learners.


The Data Analyst Professional Certificate certifies proficiency in various analytical techniques, data visualization, and dashboard creation, equipping earners for entry-level roles in data analytics. The credential is awarded upon the completion of 8 courses, where participants gain hands-on experience with tools like Excel, SQL, Python, JupyterLab, and Cognos. Badge earners demonstrate their skills by analyzing real-world datasets, creating visual reports, and presenting findings, ensuring they are ready for data analysis roles.

Salary Range

Below is a survey of average annual salaries from major job websites.

Career Overview

Job Requirements

In order to be successful in your role, these are the kinds of skills that you need to develop:

  • Data management & wrangling (organizing it into logical buckets)
  • Statistical analysis & visualization (make it easier to understand the data)
  • Model deployment & storytelling (what is it telling us about?)

Job Responsibilities:

  • Data Collection and Preprocessing:
    • Collect, clean, and preprocess data from various sources within the supply chain, including suppliers, distributors, retailers, and consumer feedback channels.
  • Process Optimization and Cost Reduction:
    • Identify opportunities for process optimization and cost reduction by analyzing data across the entire supply chain, including logistics, storage facilities, and distribution networks.
  • Quality Metrics and Feedback Analysis:
    • Monitor and analyze quality metrics and feedback data to identify areas for improvement in production and distribution processes.
  • Market Intelligence:
    • Provide market intelligence by tracking market trends, competitor activities, and consumer preferences through data analysis.
  • Reporting and Dashboard Generation:
    • Generate reports and dashboards to present findings and insights to stakeholders, including management, sales teams, and suppliers.
  • Cross-functional Collaboration:
    • Collaborate with cross-functional teams to implement data-driven solutions and drive continuous improvement in business processes.
  • Stakeholder Engagement:
    • Collaborate with various program areas to discover data and analytics needs and address them using innovative solutions.
    • Work with stakeholders to build reports and tools in line with key programmatic priorities.
    • Present insights and data-informed recommendations to help guide strategic decisions.
  • Team Management and Guidance:
    • Help manage and provide guidance to a growing team.
    • Mentor and manage a team of data analysts with varying skill levels.
  • Data Standards and Training:
    • Maintain and promote data standards to ensure proper data capture and hygiene.
    • Develop and present training materials on various tools and systems.
    • Create documentation and provide training to inform stakeholders and cultivate data literacy within the organization.
  • Data Support and Quality:
    • Develop processes for sourcing, prioritizing, and resolving data support requests from stakeholders and partners.
    • Define data quality needs to support analysis and profile data to ensure quality.
    • Implement quality monitoring and communicate the impact of data quality on analyses.
  • Business Analysis and Workflow Improvement:
    • Perform business analysis, identify root causes, and develop recommendations and solutions to drive business improvements.
    • Collaborate across departments to develop and implement improved workflows and processes.
  • Reporting and Data Management:
    • Ensure the timeliness and accuracy of internal and external report deliverables.
    • Manage scheduled and ad hoc reporting needs of the organization.
    • Execute and manage the completion of large reconciliation tasks.
    • Ensure the quality and completeness of data in core systems by performing and overseeing data audits.
    • Oversee large systems and data-related projects.
  • Analytical Projects and Business Decisions:
    • Lead and execute complex data-related analytical projects to drive business decisions and efficiencies.
    • Translate business initiatives and goals into analytical questions, identify critical metrics, conduct analysis, and develop reporting.
    • Identify relevant datasets, contribute to data transformations, clean data, and conduct exploratory and statistical analyses to identify trends or patterns.
    • Create visualizations, reports, and present findings using business intelligence applications, spreadsheets, or code.


Below are some job titles that a data analyst can become eligible for:

  • Business Analyst
  • Business Intelligence Analyst
  • Data Architect
  • Data Management
  • Data Management Specialist
  • Data Scientist
  • Deep Learning
  • Data Science Manager
  • Information Security Analyst
  • Intelligence Officer
  • Data Analytics and Reporting
  • Operations Analyst
  • Reporting Analyst