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Introduction to Data Analysis

2 Days Classroom Session   |  
2 Days Live Online
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Professional Credits


ASPE is an IIBA Endorsed Education Provider of business analysis training. Select Project Delivery courses offer IIBA continuing development units (CDU) in accordance with IIBA standards.

This course offers 14.00 IIBA CDUs.


Select courses offer Leadership (PDU-L), Strategic (PDU-S) and Technical PMI professional development units that vary according to certification. Technical PDUs are available in the following types: ACP, PBA, PfMP, PMP/PgMP, RMP, and SP.

This course offers:
    4.00 PMP/PgMP Technical PDUs
    10.00 PMI Strategic PDUs


Data Analysis is an ever-evolving discipline with lots of focus on new predictive modeling techniques coupled with rich analytical tools that keep increasing our capacity to handle big data. However, in order to chart a coherent path forward, it is necessary to understand where the discipline has come from since its inception.

The field of Business intelligence depends largely on Data analysis tools and techniques iIntroduction to Data Analysisn order to inform effective decision-making. In fact, the disciplines are so intertwined that some often confuse the two. Therefore, we begin our introduction by examining the history of Business intelligence, its relationship to data analysis, and why the two are needed to help businesses deliver a complete assembly of their 'data puzzle'. This module also addresses some of the hurdles businesses face when dealing with data overload and suggests some possible solutions to the problem.

With the explosion of big data, businesses recognize there is a greater need for employing someone who is qualified to correctly analyze the data. In this module, we explore the qualifications for the data analyst as well as the analytic tools associated with the position. It is unfortunate that there is such a dearth of data analysts. With a projected shortage of 190,000 data science jobs into 2020, it is no wonder that businesses are scrambling to recruit talent.

This ASPE course has been submitted, reviewed and approved by the International Institute of Business Analysis (IIBA) to award CDUs for attendance.

In this Introduction to Data Analysis Training Course, you will:

  • Learn the terms, jargon, and impact of business intelligence and data analytics.
  • Gain knowledge of the scope and application of data analysis.
  • Explore ways to measure the performance of and improvement opportunities for business processes.
  • Be able to describe the need for tracking and identifying the root causes of deviation or failure.
  • Review the basic principles, properties, and application of Probability Theory.
  • Discuss data distribution including Central Tendency, Variance, Normal Distribution, and non-normal distributions.
  • Learn about Statistical Inference and drawing conclusions about a Data Population.
  • Learn about Forecasting, including introduction to simple Linear Regression analysis.
  • Learn about Sample Sizes and Confidence Intervals and Limits, and how they influence the accuracy of your analysis.
  • Explore different methods and easy algorithms for forecasting future results and to reduce current and future risk.
Upcoming Dates and Locations
All Live Online times are listed in Eastern Time Guaranteed To Run
Request a quote for private onsite training Request
Sep 24, 2020 – Sep 25, 2020    9:30am – 5:30pm Live Online Register
Oct 22, 2020 – Oct 23, 2020    9:30am – 5:30pm Live Online Register
Nov 19, 2020 – Nov 20, 2020    8:30am – 4:30pm Live Online Register
Dec 17, 2020 – Dec 18, 2020    10:30am – 6:30pm Live Online Register
Jan 12, 2021 – Jan 13, 2021    8:30am – 4:30pm Chicago, Illinois

Please call ASPE for location details
at 1-877-800-5221
Chicago, IL 60601
United States

Jan 20, 2021 – Jan 21, 2021    8:30am – 4:30pm Live Online Register
Feb 4, 2021 – Feb 5, 2021    8:30am – 4:30pm Live Online Register
Feb 23, 2021 – Feb 24, 2021    8:30am – 4:30pm Oakland, California

Please call ASPE for location details
at 1-877-800-5221
United States

Mar 11, 2021 – Mar 12, 2021    8:30am – 4:30pm Jacksonville, Florida

Please call ASPE for location details
at 1-877-800-5221
Jacksonville, FL 32201
United States

Mar 22, 2021 – Mar 23, 2021    8:30am – 4:30pm Live Online Register
Apr 8, 2021 – Apr 9, 2021    8:30am – 4:30pm Boston, Massachusetts

Please call ASPE for location details
at 1-877-800-5221
Boston, MA 02101
United States

Apr 12, 2021 – Apr 13, 2021    8:30am – 4:30pm Live Online Register
May 6, 2021 – May 7, 2021    8:30am – 4:30pm Austin, Texas

Please call ASPE for location details
at 1-877-800-5221
Austin, TX 78701
United States

May 18, 2021 – May 19, 2021    8:30am – 4:30pm Live Online Register
Jun 1, 2021 – Jun 2, 2021    8:30am – 4:30pm Live Online Register
Jun 23, 2021 – Jun 24, 2021    8:30am – 4:30pm Atlanta, Georgia

Please call ASPE for location details
at 1-877-800-5221
Atlanta, GA 30301
United States

Jul 8, 2021 – Jul 9, 2021    8:30am – 4:30pm Live Online Register
Jul 19, 2021 – Jul 20, 2021    8:30am – 4:30pm Kansas City, Missouri

Please call ASPE for location details
at 1-877-800-5221
Kansas City, MO 64101
United States

Aug 10, 2021 – Aug 11, 2021    8:30am – 4:30pm Philadelphia, Pennsylvania

Please call ASPE for location details
at 1-877-800-5221
Philadelphia, PA 19101
United States

Aug 23, 2021 – Aug 24, 2021    8:30am – 4:30pm Live Online Register
Course Outline

Part 1: Data and Information

  1. Data in the Real World
  2. Data vs. Information
  3. The Many “Vs” of Data
  4. Structured Data and Unstructured Data
  5. Types of Data

Part 2: Data Analysis Defined

  1. Why do we analyze data?
  2. Data Analysis Mindset
  3. Data Analysis Steps
  4. Data Analysis Defined
  5. Descriptive Statistics vs Inferential Statistics

Part 3: Types of Variables

  1. Categorical vs Numerical
  2. Nominal Variables
  3. Ordinal Variables
  4. Interval Variables
  5. Ratio Variables

Part 4: Central Tendency of Data

  1. (Arithmetic) Mean
  2. Median
  3. Mode

Part 5: Basic Probability

  1. Probability Uses In Business
  2. Ways We Can Calculate Probability
  3. Probability Terms
  4. Calculating Probability
  5. Calculating Probability from a Contingency Table
  6. Conditional Probability
  7. Frequency Distribution

Part 6: Distributions, Variance, and Standard Deviation

  1. Discrete Distributions
  2. Continuous Distributions
  3. Range
  4. Quartiles
  5. Variance
  6. Standard Deviation
  7. Population vs. Sample
  8. Application of the Standard Deviation
    • Standard Deviation and the Normal Distribution
    • Sigma (σ) Values (Standard Deviations)
  9. Bimodal distribution
  10. Skew and Summary
  11. Other Distributions
    • Poisson Distribution
    • Exponential Distribution
    • Pareto Distribution (“80/20”)
    • Log Normal Distribution
  12. Distributions in Excel

Part 7: Fitting Data

  1. Bivariate Data (Two Variables)
  2. Covariance and Correlation
  3. Simple Linear Regression
  4. Linear Regression
  5. Fitting Functions
    • Linear Fit
    • Polynomial Fit
    • Power-Law Fit

Part 8: Predictive Analytics Overview

  1. Monte Carlo Method
Who should attend

Anyone involved in operations, project management, business analysis, or management who needs an introduction to Data Analysis, would benefit from this class:

  • Business Analyst, Business Systems Analyst, Staff Analyst
  • Those interested in CBAP®, CCBA®®, or other business analysis certifications
  • Systems, Operations Research, Marketing, and other Analysts
  • Project Manager, Team Leads, Project Leads, Project Assistants, Project Coordinators
  • Those interested in PMP®, CAPM®, or other project management certifications
  • Program Managers, Portfolio Managers, Project Management Office (PMO) staff
  • Data Modelers and Administrators, DBAs
  • Technical & other Subject Matter Experts (SMEs)
  • IT Staff, Manager, VPs
  • Finance Staff, Manager
  • Operations Analyst, Supervisor
  • External and Internal Consultants
  • Risk Managers, Operations Risk Professionals
  • Operations Managers, Line Managers, Operations Staff
  • Process Improvement, Compliance, Audit, & other Governance Staff
  • Thought Leaders, Transformation & Change Champions, Change Manager
  • Executives, Directors, & other senior staff exploring cost reduction and process improvement options
  • Executive and Administrative Assistants and Coordinators
  • Job seekers and those who want to show dedication to data analysis and process improvement
  • Leaders at all levels who wish to increase their Data Analysis capabilities

Although it is not mandatory, students who have completed the self-paced Introduction to R eLearning course have found it very helpful when completing this course.


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