Course Details

Data Analysis Training

Course description

The field of Business intelligence depends largely on Data analysis tools and techniques in order to inform effective decision-making. In fact, the disciplines are so intertwined that some often confuse the two. Therefore, we begin our introduction by examining the history of Business intelligence, its relationship to data analysis, and why the two are needed to help businesses deliver a complete assembly of their 'data puzzle'. This module also addresses some of the hurdles businesses face when dealing with data overload and suggests some possible solutions to the problem.

With the explosion of big data, businesses recognize there is a greater need for employing someone who is qualified to correctly analyze the data. In this module, we explore the qualifications for the data analyst as well as the analytic tools associated with the position.

Course outline

Part 1: Data and Information

• Data in the Real World
• Data vs. Information
• The Many “Vs” of Data
• Structured Data and Unstructured Data
• Types of Data

Part 2: Data Analysis Defined

• Why do we analyze data?
• Data Analysis Mindset
• Data Analysis Steps
• Data Analysis Defined
• Descriptive Statistics vs Inferential Statistics

Part 3: Types of Variables

• Categorical vs Numerical
• Nominal Variables
• Ordinal Variables
• Interval Variables
• Ratio Variables

Part 4: Central Tendency of Data

• (Arithmetic) Mean
• Median
• Mode

Part 5: Basic Probability

• Probability Uses In Business
• Ways We Can Calculate Probability
• Probability Terms
• Calculating Probability
• Calculating Probability from a Contingency Table

• Conditional Probability
• Frequency Distribution

Part 6: Distributions, Variance, and Standard Deviation

• Discrete Distributions
• Continuous Distributions
• Range
• Quartiles
• Variance
• Standard Deviation
• Population vs. Sample
• Application of the Standard Deviation

• Standard Deviation and the Normal Distribution
• Sigma (σ) Values (Standard Deviations)

• Bimodal distribution
• Skew and Summary
• Other Distributions

• Poisson Distribution
• Exponential Distribution
• Pareto Distribution (“80/20”)
• Log Normal Distribution

• Distributions in Excel  

Part 7: Fitting Data

• Bivariate Data (Two Variables)
• Covariance and Correlation
• Simple Linear Regression
• Linear Regression
• Fitting Functions

• Linear Fit
• Polynomial Fit
• Power-Law Fit

Part 8: Predictive Analytics Overview

• Monte Carlo Method