Data Analysis Bootcamp

1,335.00  excl. VAT

Course Code: 0004261100

Duration: 3 days;

Delivery dates: TBA;

Instructor: TBA;

Certificate: Yes, upon completion;

Location: TBA.



The Data Analysis Boot Camp equips candidates with the knowledge, techniques and models to transform data into usable insights for making business decisions. The course simplifies complex concepts, breaks down math jargon and helps navigate complex symbols and equations. These skills enable candidates to zoom in on the most useful data and apply it in the real world. It also provides practical techniques for presenting findings to quickly make decisions that drive organizations forward. These tools include graphic presentation techniques and simplified models to transform the results of data analysis into digestible, easy-to-understand insights and usable recommendations.


Anyone involved in operations, project management, business analysis, or management would benefit from this course. This training is invaluable for:

  • Business Analysts, Business Systems Analysts, CBAP, CCBA
  • Systems, Operations Research, Marketing, and other Analysts
  • Project Managers, Program Managers, Team Leaders, PMP, CAPM
  • Data Modelers and Administrators, DBAs
  • IT Managers, Directors, VPs
  • Finance Managers, Directors, VPs
  • Operations Supervisors, Managers, Directors, VPs
  • Risk Managers, Operations Risk Professionals
  • Process Improvement, Audit or Internal Consultants and Staff

Executives exploring cost reduction and process improvement options

Professionals who want to show dedication to process improvement

Senior staff who make or recommend decisions to executives


There are no prerequisites for this course. Basic familiarity with MS Excel or a similar tool is recommended.

Course Materials

ITPRENEURS. ASPE.  0004261100

Course Description

  • Identify opportunities, manage change and develop deep visibility into the organization
  • Understand analytics, business intelligence and statistics terminology
  • Practical applications of data analysis across business
  • Data visualization and effective presentation of data analysis results
  • Create more accurate projections while accounting for variance, error, and confidence intervals
  • Using the array of data plots and chart formats to analyse underlying data trends and patterns through practical exercises
  • Differentiating data signal from data noise – separating critical from extraneous data
  • Understand and leverage different distribution models, and the real world applications
  • In-depth practical statistics knowledge, and how it relates to risk, probability, results and action
  • Develop a robust, practical understanding of probability theory – and how to leverage it
  • Form and test hypotheses – using multiple methods to define and interpret projections
  • Statistical inference and interpretation of population wide conclusions
  • Substantial set of practical modeling skills
  • Using computation to mine data, run simulations, find data clusters and critical attributes
  • Application of data for practical use: Reporting, Dashboards, Metrics, Quality, Financial Modeling and more
  • Hands-on predictive analytics knowledge including key terminology and algorithms
  • Forecasting future results, finding opportunities for process improvement, and analyzing past performance
  • Real-world labs using data analysis tools as per the course syllabus
  • Applicability of data analysis skills and methods to candidates’ own scenarios with a data expert instructor over the three days

Course Outline

Data Fundamentals

  • Course Overview and Level Set
  • Understanding Real-world Data
  • Types of Data
  • LAB: Hands-on – Profiling Data
  • Data-related Risk
  • Data Quality
  • LAB: Hands-on – Dealing with Duplicates
  • Relationships
  • LAB: Hands-On – Data Relationships using PowerPivot

Analysis Foundations

  • Statistical Practices: Overview
  • Domains of Data Analysis
  • Analyzing Data
  • Statistical Practices: Overview
  • Averages in Data
  • Central Tendency
  • LAB: Hands-On – Central Tendency
  • LAB: Hands-On – Linear Regression
  • Distributions
  • Correlation
  • LAB: Hands-On – Distributions in Consumer Finance Data
  • Analytical Graphics for Data

Analytics & Modeling

  • ROI & Financial Decisions
  • LAB: Hands-On – Helpful Financial Metrics in Excel
  • Using Financial Data
  • Random Numbers
  • Demo / Lab – Monte Carlo Analysis in Excel
  • Predictive Analytics
  • Demo / Lab – Using R for Powerful Analysis
  • Clustering
  • Data Modeling
  • Data Warehousing

Visualizing & Presenting Data

  • Goals of Visualization
  • Visualization Essentials
  • Demo / Lab – Improving a Difficult Report
  • Communicating Data-Driven Knowledge