Data Analysis Boot Camp

3 Day Classroom  •  3 Day Live Online
3 Day Training at your location.
Adjustable to meet your needs.
Individual:
$1995.00
Group Rate:
$1795.00
GSA Discount:
$1456.35
When training eight or more people, onsite team training offers a more affordable and convenient option.
Register Now
Request Quote
Individual
Onsite
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 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.

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

data analysis training courseThis 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
Sep 17, 2018 – Sep 19, 2018    8:30am – 4:30pm Live Online
8:30am – 4:30pm
Register
Oct 1, 2018 – Oct 3, 2018    8:30am – 4:30pm Los Angeles, California

Please call ASPE for location details
at 1-877-800-5221
Los Angeles, CA 90001
United States

Register
Oct 15, 2018 – Oct 17, 2018    8:30am – 4:30pm Live Online
8:30am – 4:30pm
Register
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

Register
Oct 22, 2018 – Oct 24, 2018    8:30am – 4:30pm Denver, Colorado

Microtek Denver
999 18th Street
Suite 300 South Tower
Denver, CO 80202
United States

Register
Oct 22, 2018 – Oct 24, 2018    10:30am – 6:30pm Live Online
10:30am – 6:30pm
Register
Nov 5, 2018 – Nov 7, 2018    8:30am – 4:30pm Chicago, Illinois

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

Register
Nov 12, 2018 – Nov 14, 2018    8:30am – 4:30pm Seattle, Washington

Allied Business Systems - Computer Classrooms
10604 NE 38th Place, Suite 118
Yarrow Bay Office Park-1 North
Kirkland, WA 98033
United States

Register
Nov 12, 2018 – Nov 14, 2018    11:30am – 7:30pm Live Online
11:30am – 7:30pm
Register
Dec 3, 2018 – Dec 5, 2018    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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
10:30am – 5:30pm
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