Data Analysis Boot Camp Classroom Live Kansas City, MO July 27, 2020

Price: $1,900

This course runs for a duration of .

The class will run daily from 8:30 am CST to 4:30 pm CST.

Class Location: Kansas City - Kansas City, MO.

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Description

This three-day course, organized into key topic areas, leverages straightforward business examples to explain practical techniques for understanding and reviewing data quality. You will learn how to make more informed, intelligent business decisions by analyzing data using Excel functions and the R programming language.

You will 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 decisions that drive your organization forward.

Who Should Attend:

This data analysis training course is designed for the following professions:

  • 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

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

This data analyst 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.

In This Data Analysis Training Course, You Will: 

  • 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

Course Overview

Part 1: Data Fundementals

  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

Prerequisites

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.

Other Available Dates for this Course

Classroom Live
December 16, 2019

Burlington, MA
$1,900.00
   8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
January 21, 2020

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Classroom Live
January 21, 2020

Raleigh, NC
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Classroom Live
January 27, 2020

Boston, MA
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Classroom Live
February 18, 2020

Denver, CO
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Virtual Classroom Live
February 18, 2020

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Classroom Live
February 24, 2020

San Francisco, CA
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   8:30 am PST - 4:30 pm PST
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Virtual Classroom Live
March 23, 2020

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Classroom Live
March 23, 2020

Atlanta, GA
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Classroom Live
March 30, 2020

Austin, TX
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Classroom Live
April 20, 2020

Philadelphia, PA
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Classroom Live
April 27, 2020

San Jose, CA
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Virtual Classroom Live
April 27, 2020

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Classroom Live
May 18, 2020

Houston, TX
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Virtual Classroom Live
May 18, 2020

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Classroom Live
May 27, 2020

Minneapolis, MN
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Virtual Classroom Live
June 22, 2020

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Classroom Live
June 22, 2020

Reston, VA
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Classroom Live
June 29, 2020

Columbus, OH
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Virtual Classroom Live
July 20, 2020

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Classroom Live
July 20, 2020

Jacksonville, FL
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Classroom Live
August 17, 2020

Detroit, MI
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Virtual Classroom Live
August 17, 2020

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Classroom Live
August 31, 2020

Seattle, WA
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   8:30 am PST - 4:30 pm PST
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Virtual Classroom Live
August 31, 2020

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Classroom Live
September 14, 2020

Denver, CO
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   8:30 am MST - 4:30 pm MST
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Virtual Classroom Live
September 14, 2020

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Classroom Live
September 21, 2020

Albany, NY
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Classroom Live
September 28, 2020

Baltimore, MD
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Classroom Live
October 13, 2020

Salt Lake City, UT
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   8:30 am PST - 4:30 pm PST
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Virtual Classroom Live
October 13, 2020

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Classroom Live
October 19, 2020

Chicago, IL
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Classroom Live
October 26, 2020

Dallas, TX
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Virtual Classroom Live
October 26, 2020

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Classroom Live
November 09, 2020

St. Louis, MO
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Virtual Classroom Live
November 09, 2020

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Classroom Live
November 16, 2020

Washington, DC
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Classroom Live
December 07, 2020

Cincinnati, OH
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Virtual Classroom Live
December 07, 2020

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Classroom Live
December 14, 2020

Portland, OR
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   8:30 am PST - 4:30 pm PST
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