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.
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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.

Labs for this course are primarily in Microsoft Excel, however, students will get an opportunity to practice using R in some labs. Labs for this course can also be taught using the Python programming language for private onsite clients only.

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
Aug 19, 2019 – Aug 21, 2019    8:30am – 4:30pm Minneapolis, Minnesota Register
Aug 19, 2019 – Aug 21, 2019    9:30am – 5:30pm Live Online
9:30am – 5:30pm
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Sep 9, 2019 – Sep 11, 2019    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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Sep 9, 2019 – Sep 11, 2019    8:30am – 4:30pm Philadelphia, Pennsylvania

Hyatt Place
440 American Avenue
King Of Prussia, PA 19406
United States

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Sep 16, 2019 – Sep 18, 2019    8:30am – 4:30pm Kansas City, Missouri

Centriq Training
1740 W 92nd Street
Kansas City, MO 64114
United States

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Sep 23, 2019 – Sep 25, 2019    8:30am – 4:30pm Raleigh, North Carolina

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

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Sep 23, 2019 – Sep 25, 2019    9:00am – 5:00pm Live Online
9:00am – 5:00pm
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Oct 2, 2019 – Oct 4, 2019    8:30am – 4:30pm Austin, Texas

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

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Oct 2, 2019 – Oct 4, 2019    9:30am – 5:30pm Live Online
9:30am – 5:30pm
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Oct 21, 2019 – Oct 23, 2019    8:30am – 4:30pm Chicago, Illinois

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

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Oct 28, 2019 – Oct 30, 2019    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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Oct 28, 2019 – Oct 30, 2019    8:30am – 4:30pm Jacksonville, Florida

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

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Nov 4, 2019 – Nov 6, 2019    8:30am – 4:30pm San Jose, California

Please call ASPE for location details
at 1-877-800-5221
San Jose, CA 95101
United States

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Nov 11, 2019 – Nov 13, 2019    8:30am – 4:30pm Phoenix, Arizona

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

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Nov 11, 2019 – Nov 13, 2019    11:30am – 7:30pm Live Online
11:30am – 7:30pm
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Nov 18, 2019 – Nov 20, 2019    8:30am – 4:30pm Columbia, Maryland

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

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Dec 9, 2019 – Dec 11, 2019    8:30am – 4:30pm Houston, Texas

Texas Training and Conference
11490 Westheimer Rd.
Suite 600
Houston, TX 77077
United States

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Dec 9, 2019 – Dec 11, 2019    9:30am – 5:30pm Live Online
9:30am – 5:30pm
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Dec 16, 2019 – Dec 18, 2019    8:30am – 4:30pm Boston, Massachusetts

Microtek Boston
25 Burlington Mall Road
2nd Floor
Burlington, MA 01803
United States

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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