Fundamentals of Data Analytics Training

Course #:TP2360

Fundamentals of Data Analytics Training

In 2006, Tom Davenport wrote an article for Harvard Business Review titled Competing on Analytics.  Even a few short years ago, Data Analytics was a specialized skill set.  Since then much has changed.  New technologies can handle the volume, velocity and variety of Big Data, data mining techniques have improved, and tools have the capacity and capability to move analytics from specialist to business users.  In turn, companies are leveraging these abilities to move from intuition to data-based decision-making.  This course is designed to bring managers and analyst up to speed with the current thinking and techniques used to guide data analytics projects.

Why Attend this Course?

  • What can I do as a business analyst and when do I need to start learning specialized data analytics skills?
  • This course examines several depictions of data analytics and defines boundaries that can define the need for specialized skills
  • Many analysts start their analysis by opening EXCEL. 
  • There is a process that should be followed for data analytics projects.  This will be introduced and utilized during class.
  • Recommendations are typically buried in misunderstood charts and tables upon tables of data.
  • This course introduces four principles for data visualizations – graphics that help find the unexpected and communicate data as insights.

What Makes this Course Stand Apart?

  • The course is constructed around common data analytics competencies.
  • A case study approach links together the various topics discussed.
  • Hands-on exercises challenge participants with issues faced during typical analytics projects.
  • Covers the very latest ‘thinking’ in data analytics.

What You Will Learn

Upon completion of this course you will be able to:

  • Distinguish between different types of data analytics projects.
  • Understand the key challenges of data analytics projects.
  • Define the key attributes of companies that compete on analytics.
  • Use a portfolio of examples to recognize opportunities within your company.
  • Critique visualizations as a means of improving their communication abilities.


  • Business Analyst (IT and non-IT)
  • Data Quality Analyst
  • Database Administrators
  • Project Leaders
  • Systems Analyst
  • Data Analyst


The structure of the courses assumes no prior experience in statistics or data analytics. 


1 day

Outline of Fundamentals of Data Analytics Training

1. Big Data

  • Big Data/Social Media Data/Industrial Data
  • Volume, Velocity, Variety & Variability 
  • Challenges & Opportunities with Big Data

2. Data Analytics

  • Types of Analytics Projects with real world examples
  • Common Competencies and Skills
  • A Process for Analytics
  • Common Challenges
  • Data Mining Techniques (An Overview)

3. Data Visualization

  • Pre-attentive Processing
  • Data Types and Visual Attributes
  • Critiquing Visualizations for Improvement
We regularly offer classes in these and other cities. Atlanta, Austin, Baltimore, Calgary, Chicago, Cleveland, Dallas, Denver, Detroit, Houston, Jacksonville, Miami, Montreal, New York City, Orlando, Ottawa, Philadelphia, Phoenix, Pittsburgh, Seattle, Toronto, Vancouver, Washington DC.