Analytics: Your Gateway to Transforming Data into Impact

The global data analytics landscape is evolving faster than ever. Fueled by advances in AI, machine learning and real-time decision-making; the industry is expected to exceed $650 billion by 2029, with an emphasis on automation, domain-specific applications and responsible use of data.

In today's dynamic business environment, organizations leverage data not just to understand the past, but to predict the future and shape outcomes. Read on to discover career paths, skills, and the new frontiers in analytics.

Where You Might Work

  • Big Data and Business Analytics
  • Real-Time and Edge Analytics
  • Digital Twins and Internet of Things (IoT)
  • Augmented and Embedded Business Intelligence
  • Machine Learning, Artificial Intelligence (AI), and Predictive Analytics
  • Cognitive and Conversational Analytics
  • Responsible AI and Data Privacy Compliance

Sample Job Titles

  • Business Analyst
  • Data Analyst
  • Machine Learning Engineer
  • MLOps Engineer
  • Data Engineer
  • Business Intelligence Analyst
  • Data Governance Specialist
  • AI Product Manager
  • Information Architect

Top Career Paths in Analytics

Types Of Data Analytics

  • Descriptive Analytics: Understand what happened.
  • Diagnostic Analytics: Understand why it happened.
  • Predictive Analytics: Forecast what could happen.
  • Prescriptive Analytics: Suggest actions based on predictions.
  • Cognitive Analytics: Use AI to simulate human thought processes.
  • Real-Time Analytics: Drive instant decision-making from live data streams.

Top Industries Where Analytics is Transforming Business

  1. Health Care and Life Sciences
  2. Financial Services and FinTech
  3. Energy and Climate Technology
  4. Cybersecurity and Risk Management
  5. Supply Chain and Logistics
  6. Retail and E-commerce
  7. Government and Smart Cities
  8. Media and Entertainment
  9. Manufacturing (Industry 4.0)
  10. Education Technology (EdTech)

Breaking into Analytics: Resources and Skills

To succeed, you'll need a strong foundation in business acumen, programming, and emerging technologies. Core skills include:

  • Python, SQL, R
  • Statistics and Probability
  • Data Visualization (Tableau, Power BI)
  • Machine Learning Frameworks (TensorFlow, Scikit-Learn)
  • Cloud Platforms (AWS, Azure, GCP)

Recommended Learning Platforms:

Academics

To learn more about the Analytics areas and courses included within the concentration or program, please refer to the academic curriculum.