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Data Analysis Boot Camp


3 Days Classroom Session   |  
3 Days Live Online
Classroom Registration
Individual:
$1995.00
Group Rate:
$1795.00
(per registrant, 2 or more)
GSA Individual:
$1456.35
Live Online Registration
Live Online:
$1995.00
Private Onsite Package

This course can be tailored to your needs for private, onsite delivery at your location.

Request a Private Onsite Price Quote

Professional Credits

IIBA (CDU)

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.

PMI (PDU)

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:
    21.00 PMP/PgMP Technical PDUs

21
PMI PDUs
Certification
Overview

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 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 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.

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.

*Please note, if you are taking this class as part of the St. Louis University Certificate requirements, there is a $500 fee to claim your certificate once you have completed ALL requirements.

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
All Live Online times are listed in Eastern Time Guaranteed To Run
Nov 12, 2018 – Nov 14, 2018    11:30am – 7:30pm Live Online Register
Dec 3, 2018 – Dec 5, 2018    8:30am – 4:30pm Live Online Register
Dec 3, 2018 – Dec 5, 2018    8:30am – 4:30pm Reston, Virginia

Homewood Suites Dulles Airport
13460 Sunrise Valley Drive
Herndon, VA 20171
United States

Register
Dec 10, 2018 – Dec 12, 2018    8:30am – 4:30pm San Francisco, California

Learn IT
33 New Montgomery St.
Suite 300
San Francisco, CA 94105
United States

Register
Dec 17, 2018 – Dec 19, 2018    10:30am – 5:30pm Live Online Register
Jan 22, 2019 – Jan 24, 2019    8:30am – 4:30pm Kansas City, Kansas

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

Register
Jan 22, 2019 – Jan 24, 2019    9:30am – 5:30pm Live Online Register
Jan 28, 2019 – Jan 30, 2019    8:30am – 4:30pm Jacksonville, Florida

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

Register
Feb 19, 2019 – Feb 21, 2019    8:30am – 4:30pm Chicago, Illinois

Microtek Chicago
230 W. Monroe
Suite 900
Chicago, IL 60606
United States

Register
Feb 25, 2019 – Feb 27, 2019    8:30am – 4:30pm San Jose, California

ExecuTrain West
2025 Gateway Place
Suite 390
San Jose, CA 95110
United States

Register
Feb 25, 2019 – Feb 27, 2019    11:30am – 7:30pm Live Online Register
Mar 18, 2019 – Mar 20, 2019    8:30am – 4:30pm Raleigh, North Carolina

ASPE Training
2000 Regency Parkway
Suite 335
Cary, NC 27518
United States

Register
Mar 25, 2019 – Mar 27, 2019    8:30am – 4:30pm Minneapolis, Minnesota

Embassy Suites Airport
7901 34th Avenue South
Bloomington, MN 55425
United States

Register
Mar 25, 2019 – Mar 27, 2019    9:30am – 5:30pm Live Online Register
Apr 22, 2019 – Apr 24, 2019    8:30am – 4:30pm Austin, Texas

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

Register
Apr 22, 2019 – Apr 24, 2019    9:30am – 5:30pm Live Online Register
Apr 29, 2019 – May 1, 2019    8:30am – 4:30pm Columbia, Maryland

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

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May 20, 2019 – May 22, 2019    8:30am – 4:30pm Sacramento, California

UC Davis
2901 K Street, Ste 204
Sutter Square Galleria
Sacramento, CA 95816
United States

Register
May 20, 2019 – May 22, 2019    11:30am – 7:30pm Live Online Register
May 29, 2019 – May 31, 2019    8:30am – 4:30pm Omaha, Nebraska

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

Register
Course Outline

Part 1: Data Fundamentals

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

Part 2: Analysis Foundations

  1. 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

Part 3: Analyzing Data

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

Part 4: Analytics & Modeling

  1. 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
  2. Understanding Clustering
  3. Segmentation
  4. Common Algorithms
  5. K-MEANS

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

  1. R Basics
  2. Descriptive Statistics
  3. Importing and Manipulating Data
  4. R Scripting
  5. Data Visualization with R
  6. Regression in R
  7. K-MEANS in R
  8. Monte Carlo in R
  9. Demo/Lab: Hands-on R work

Part 6: Visualizing & Presenting Data

  1. Goals of Visualization
    • Communication and Narrative
    • Decision Enablement
    • Critical Characteristics
  2. Visualization Essentials
    • Users and Stakeholders
    • Stakeholder Cheat Sheet
    • Common Missteps
  3. 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
Pre-Requisites

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.

Download the brochure