Data Analysis Boot Camp

3 Day Classroom  •  3 Day Live Online
3 Day Training at your location.
Adjustable to meet your needs.
Group Rate:
GSA Discount:
When training eight or more people, onsite team training offers a more affordable and convenient option.
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Every day buzzwords like "analytics," "insights" and "big data," permeate the pages of our business journals. Companies and departments are well aware of their huge troves of data, and they have access to common tools for leveraging this data. However, much less available are the actual analysis skills to truly understand and realize the benefits of this information. The potential is very real, but comprehensive skills can be scarce, and outside consultants are expensive. If you have a basic familiarity with Excel, this three-day course can teach you practical applied analysis techniques to leverage data for relatively common decision-making methods.

This course, organized into key topic areas, leverages straightforward business examples to explain practical techniques for understanding and reviewing data quality and how to translate data into the analysis of business problems to begin making informed intelligent decisions. Get an overview of data quality and data management, followed by foundational analysis and statistical techniques. Throughout the course, you will learn to communicate about data and findings to stakeholders who need to quickly make the decisions that drive your organization forward.

Our instructor did a fantastic job and I felt he tailored the lesson to everyone's needs, even on a 1 on 1 basis when needed.
Mike Mullenix, Education Affiliates 

At the end of the class, we provide an overview of the Certified Analytics Professional certification. We discuss business applications for professionals with the certification, the main focus areas behind the certification, test-preparation and test-taking anecdotes.

Informs logo ASPE Training is proud to announce that we are an official Registered Education Provider (REP) with Informs® for the Certified Analytics Professional (CAP®) Exam.

In–Class Exercises, Demos, and Real-World Case Studies

This data analysis training class is a lively blend of expert instruction combined with hands-on exercises so you can practice new skills. Leave prepared to start performing practical analysis techniques the moment you return to work. Every Data Analysis Boot Camp instructor is a veteran consultant and data guru who will guide you through effective best practices and easily-accessible technologies for working with your data. Through a combination of demonstrations and hands-on practice, you will learn to use data analysis techniques which are typically the domain of expensive consultants.

Techtown is a division of ASPE Training, an Endorsed Education Provider (EEP), this ASPE course has been submitted, reviewed and approved by the International Institute of Business Analysis (IIBA) to award CDUs for attendance.

Identify opportunities, manage change and develop deep visibility into your organization
Understand the terminology and jargon of analytics, business intelligence and statistics
Learn a wealth of practical applications for applying data analysis capability
Visualize both data and the results of your analysis for straightforward graphical presentation to stakeholders
Learn to estimate more accurately than ever, while accounting for variance, error, and Confidence Intervals
Practice creating a valuable array of plots and charts to reveal hidden trends and patterns in your data
Differentiate between "signal" and "noise" in your data
Understand and leverage different distribution models, and how each applies in the real world
Form and test hypotheses – use multiple methods to define and interpret useful predictions
Learn about statistical inference and drawing conclusions about the population
Upcoming Dates and Locations
Guaranteed To Run
Mar 19, 2018 – Mar 21, 2018    9:30am – 5:30pm Live Online
9:30am – 5:30pm
Apr 16, 2018 – Apr 18, 2018    8:30am – 4:30pm Omaha, Nebraska

Doubletree Hotel & Executive Meeting Center
1616 Dodge Street
Omaha, NE 68102
United States

Apr 23, 2018 – Apr 25, 2018    8:30am – 4:30pm Sacramento, California

UC Davis Extension, Sutter Square Galleria Center
2901 K St
Room 305
Sacramento, CA 95816
United States

Apr 23, 2018 – Apr 25, 2018    11:30am – 7:30pm Live Online
11:30am – 7:30pm
May 14, 2018 – May 16, 2018    8:30am – 4:30pm Jacksonville, Florida

Holiday Inn Baymeadows
11083 Nurseryfields Drive
Jacksonville, FL 32256
United States

May 21, 2018 – May 23, 2018    8:30am – 4:30pm Dallas, Texas

Microtek Dallas
5430 Lyndon B Johnson Fwy
Three Lincoln Centre, Suite 300
Dallas, TX 75240
United States

May 21, 2018 – May 23, 2018    9:30am – 5:30pm Live Online
9:30am – 5:30pm
Jun 11, 2018 – Jun 13, 2018    8:30am – 4:30pm Baltimore, Maryland

Mt Washington Conference Ctr
5801 Smith Ave
Baltimore, MD 21209
United States

Jun 18, 2018 – Jun 20, 2018    8:30am – 4:30pm Phoenix, Arizona

Dynamic Worldwide
4500 S. Lakeshore Dr
Suite 600
Tempe, AZ 85282
United States

Jun 18, 2018 – Jun 20, 2018    10:30am – 6:30pm Live Online
10:30am – 6:30pm
Jul 16, 2018 – Jul 18, 2018    8:30am – 4:30pm Kansas City, Kansas

Centriq Training
8700 State Line Road
Suite 200
Leawood, KS 66206
United States

Jul 23, 2018 – Jul 25, 2018    8:30am – 4:30pm Live Online
8:30am – 4:30pm
Jul 23, 2018 – Jul 25, 2018    8:30am – 4:30pm Washington, District of Columbia

Microtek-Washington, DC
1110 Vermont Avenue NW
Suite 700
Washington, DC 20005
United States

Aug 13, 2018 – Aug 15, 2018    8:30am – 4:30pm Minneapolis, Minnesota

Euler Training Center
1660 Highway 100 S
Ste 101 - Parkdale Plaza
Minneapolis, MN 55416
United States

Aug 13, 2018 – Aug 15, 2018    9:30am – 5:30pm Live Online
9:30am – 5:30pm
Aug 20, 2018 – Aug 22, 2018    8:30am – 4:30pm Atlanta, Georgia

Microtek Atlanta
1000 Abernathy Rd. NE Ste 194
Northpark Bldg 400
Atlanta, GA 30328
United States

Sep 12, 2018 – Sep 14, 2018    8:30am – 4:30pm Austin, Texas

Embassy Suites Austin Central
5901 North IH-35
Frontage Rd
Austin, TX 78723
United States

Sep 17, 2018 – Sep 19, 2018    8:30am – 4:30pm Live Online
8:30am – 4:30pm
Sep 17, 2018 – Sep 19, 2018    8:30am – 4:30pm Columbia, Maryland

Homewood Suites by Hilton
8320 Benson Drive
Columbia, MD 21045
United States

Oct 15, 2018 – Oct 17, 2018    8:30am – 4:30pm Raleigh, North Carolina

ASPE Training
114 Edinburgh South Dr
Suite 200
Cary, NC 27511
United States

Course Outline

Section 1: Data Fundamentals

  • Course Overview and Level Set
    • Objectives of the Class
    • Expectations for the Class
  • Understanding “Real-World” Data
    • Unstructured vs. Structured
    • Relationships
    • Outliers
    • Data growth
  • Types of Data
    • Flavors of Data
    • Sources of Data
    • Internal vs. External Data
    • Time Scope of Data (Lagging, Current, Leading)
  • LAB: Get Started with our Classroom Data
  • Data-Related Risk
    • Common Identified Risks
    • Effect of Process on Results
    • Effect of Usage on Results
    • Opportunity Costs, Tool Investment
    • Mitigation of Risk
  • Data Quality
    • Cleansing
    • Duplicates
    • SSOT
    • Field standardization
    • Identify sparsely populated fields
    • How to fix common issues
  • LAB: Data Quality

Section 2: Analysis Foundations

  • Statistical Practices: Overview
    • Comparing Programs and Tools
    • Words in English vs. Data
    • Concepts Specific to Data Analysis
    • Domains of Data Analysis
    • Descriptive Statistics
    • Inferential Statistics
    • Analytical Mindset
    • Describing and Solving Problems

Section 3: Analyzing Data

  • Averages in Data
    • Mean
    • Median
    • Mode
    • Range
  • Central Tendency
    • Variance
    • Standard Deviation
    • Sigma Values
    • Percentiles
    • Use Concepts for Estimating
  • LAB: Hands-On – Central Tendency
  • Analytical Graphics for Data
  • Categorical
    • Bar Charts
  • Continuous
    • Histograms
  • Time Series
    • Line Charts
  • Bivariate Data
    • Scatter Plots
  • Distribution
    • Box Plot

Section 4: Analytics & Modeling

  • Overview of Commonly Useful Distributions
    • Probability Distribution
    • Cumulative Distribution
    • Bimodal Distributions
    • Skewness of Data
    • Pareto Distribution
      • Correlation
    • LAB: Distributions
    • Predictive Analytics
    • A Discussion about Patterns
    • Regression and Time Series for Prediction
    • LAB: Hands-On – Linear Regression
      • Simulation
    • Pseudo-random Sequences
    • Monte Carlo Analysis
    • Demo / Lab: Monte Carlo in Excel
  • Understanding Clustering
  • Segmentation
  • Common Algorithms

Section 5: Hands-On Introduction to R and R Studio

  • R Basics
  • Descriptive Statistics
  • Importing and Manipulating Data
  • R Scripting
  • Data Visualization with R
  • Regression in R
  • K-MEANS in R
  • Monte Carlo in R
  • Demo/Lab: Hands-on R work

Section 6: Visualizing & Presenting Data

  • Goals of Visualization
    • Communication and Narrative
    • Decision Enablement
    • Critical Characteristics
  • Visualization Essentials
    • Users and Stakeholders
    • Stakeholder Cheat Sheet
    • Common Missteps
  • Communicating Data-Driven Knowledge
    • Alerting and Trending
    • To Self-Serve or Not
    • Formats & Presentation Tools
    • Design Considerations
Who should attend
  • Business Analyst, Business Systems Analyst, CBAP, CCBA
  • Systems, Operations Research, Marketing, and other Analysts
  • Project Manager, Program Manager, Team Leader, PMP, CAPM
  • Data Modelers and Administrators, DBAs
  • IT Manager, Director, VP
  • Finance Manager, Director, VP
  • Operations Supervisor, Manager, Director, VP
  • Risk Managers, Operations Risk Professionals
  • Process Improvement, Audit, Internal Consultants and Staff
  • Executives exploring cost reduction and process improvement options
  • Job seekers and those who want to show dedication to process improvement
  • Senior staff who make or recommend decisions to executives

If you have basic familiarity with Excel, this three-day course can teach you practical applied analysis techniques to leverage data for relatively common decision making methods.

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