Data Analysis Boot Camp

Course Details
Code: 2397
Tuition (USD): $1,995.00 • Virtual (3 days)
$1,995.00 • Classroom (3 days)

In this fast-paced classroom experience, you will learn how to use your data to deal with critical factors: risk, performance, quality, forecasting, estimating, simulation, business process improvement, and much more. You will learn how to perform practical analytics, modeling, and interpretation the moment you return to work. Through a combination of demonstrations and hands-on exercises, you will get practice with the sort of skills and techniques which are typically the domain of expensive consultants.

You will quickly master powerful skills and the technologies to deploy them without reliance on proprietary technology. (We teach data skills you can deploy using Excel, R, or Python). Working through these scenarios, you will learn the value of analytics in supporting decision-making processes and the management and controls of business processes. In addition to providing real-world data analysis skills and concepts, you will apply the knowledge you acquire in a number of real business scenarios to learn practical applications.

Suggested Audience

Skills Gained

  • Identify opportunities, manage change, and develop deep visibility into your organization
  • Terminology and jargon of analytics, business intelligence, and statistics
  • Applications for applying data analysis capability
  • Visualize both data and the results of your analysis for straightforward graphical presentation to stakeholders
  • Estimate more accurately while accounting for variance, error, and confidence intervals
  • Create plots and charts to reveal hidden trends and patterns in your data
  • Differentiate between "signal" and "noise" in your data to smooth what's extraneous and reveal what's important
  • Different distribution models and how each applies in the real world
  • Practical statistics and how they relate to risk, probability, results, and action
  • Develop a robust, practical understanding of probability theory - and how to leverage it
  • Form and test hypotheses - use multiple methods to define and interpret useful predictions
  • Learn about statistical inference and drawing conclusions about the population
  • Leave class with a substantial yet practical toolbox of modeling skills
  • Use computation to mine data, run simulations, find clusters and discover important attributes
  • Apply your data to practical uses: Reporting, Dashboards, Metrics, Quality, Financial Modeling and more
  • Get hands-on with predictive analytics - leave class with the vocabulary and algorithms you need
  • Forecast future results, find opportunities for process improvement, and analyze past performance
  • Introduction to the INFORMS CAP (Certified Analytics Professional) certification
  • Investigate a number of real-world examples that bring to life the new tools you've learned
  • Over three days, get access to a real-world data expert who relates skills and methods to your own scenario

Who Can Benefit

  • Business analyst, business systems analyst, CBA, CCB
  • Systems, operations research, marketing, and other analysts
  • Project manager, program manager, team leader, PM, CAP
  • 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

Course Details

1. Statistics: Understanding Data

  • Statistical Thinking Overview
  • Descriptive Statistics
  • Cumulative Distribution Functions
  • Continuous Distributions
  • Probability
  • Operations on Distributions
  • Hypothesis Testing
  • Estimation
  • Correlation

2. Graphics: Looking at Data

  • Single Variable: Establishing Distribution
  • Two Variables: Establishing Relationships
  • Time-series Analysis
  • More than Two Variables

3. Analytics: Modeling Data

  • 'Guesstimation'
  • Models from Scaling Arguments
  • Arguments from Probability Models

4. Computation: Mining Data

  • Simulations
  • Finding Clusters
  • Finding Important Attributes

5. Applications: Using Data

  • Reporting, Business Intelligence, and Dashboards
  • Financial Calculations and Modeling
  • Predictive Analytics

6. CAP Certification Overview

  • The Seven Analytics Domains
    • Business Problem Framing
    • Analytics Problem Framing
    • Data
    • Methodology (Approach) Selection
    • Model Building
    • Solution Deployment
    • Model Lifecycle
  • Test Preparation Advice
  • Test Experience Feedback

7. Course Summary:

  • Understanding, Analyzing, and Presenting Data
    • Statistics
    • Graphics
    • Analytics
    • Computing
    • Applications
  • Certified Analytics Professional
  • Student Feedback / Evaluations
  • Networking

8. Decision Support

  • Scope of the decision and measure of performance
  • Controllable and uncontrollable variables
  • Uncertainty and risk analysis
  • What if analysis
  • Identification and description of needed information types

9. Data Mining and Data Warehousing

  • Data mining concepts and application
  • Application benefits of data warehousing

Exercises:

Exercise 6: This group exercise will provide you with information on the scope of a given decision and the additional facts required for you to document the controllable variables and the measure of performance. Additional information will be provided on the history of results and the occurrence of a set of independent variables to select the critical independent variables impacting the decision. You will estimate the uncertainty and describe the risks. Information will be provided to determine the degree of uncertainty and associated risks. The required information needed to support the given decision and the impact on the data requirements will be documented.