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
Dec 9, 2019 – Dec 11, 2019    9:30am – 5:30pm Live Online
9:30am – 5:30pm
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Jan 21, 2020 – Jan 23, 2020    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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Jan 21, 2020 – Jan 23, 2020    8:30am – 4:30pm Raleigh, North Carolina

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

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Jan 27, 2020 – Jan 29, 2020    8:30am – 4:30pm Boston, Massachusetts

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

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Feb 18, 2020 – Feb 20, 2020    8:30am – 4:30pm Denver, Colorado

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

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Feb 18, 2020 – Feb 20, 2020    10:30am – 6:30pm Live Online
10:30am – 6:30pm
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Feb 24, 2020 – Feb 26, 2020    8:30am – 4:30pm San Francisco, California

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

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Mar 23, 2020 – Mar 25, 2020    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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Mar 23, 2020 – Mar 25, 2020    8:30am – 4:30pm Atlanta, Georgia

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

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Mar 30, 2020 – Apr 1, 2020    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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Apr 20, 2020 – Apr 22, 2020    8:30am – 4:30pm Philadelphia, Pennsylvania

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

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Apr 27, 2020 – Apr 29, 2020    8:30am – 4:30pm San Jose, California

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

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Apr 27, 2020 – Apr 29, 2020    11:30am – 7:30pm Live Online
11:30am – 7:30pm
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May 18, 2020 – May 20, 2020    8:30am – 4:30pm Houston, Texas

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

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May 18, 2020 – May 20, 2020    9:30am – 5:30pm Live Online
9:30am – 5:30pm
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May 27, 2020 – May 29, 2020    8:30am – 4:30pm Minneapolis, Minnesota

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

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Jun 22, 2020 – Jun 24, 2020    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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Jun 22, 2020 – Jun 24, 2020    8:30am – 4:30pm Reston, Virginia

Attune, formerly Microtek Reston
12950 Worldgate Drive
Monument II Bldg 4th Flr
Herndon, VA 20170
United States

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Jun 29, 2020 – Jul 1, 2020    8:30am – 4:30pm Columbus, Ohio

The Fawcett Center
2400 Olentangy River Rd
Columbus, OH 43210
United States

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Jul 20, 2020 – Jul 22, 2020    8:30am – 4:30pm Live Online
8:30am – 4:30pm
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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