Introduction to Data Analysis

With the explosion of big data, businesses recognize there is a greater need to employ 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. It is unfortunate that there is such a dearth of data analysts.

• Learn the terms, jargon, and impact of business intelligence and data analytics.

• Gain knowledge of the scope and application of data analysis.

• Explore ways to measure the performance of and improvement opportunities for business processes.

• Be able to describe the need for tracking and identifying the root causes of deviation or failure.

• Review the basic principles, properties, and application of probability theory.

• Discuss data distribution, including central tendency, variance, normal distribution, and non-normal distributions.

• Learn about statistical inference and drawing conclusions about a data population.

• Learn about forecasting, including an introduction to simple linear regression analysis.

• Learn about sample sizes, confidence intervals, and limits, and how they influence the accuracy of your analysis.

• Explore different methods and easy algorithms for forecasting future results and reducing current and future risk.

Audience

Anyone involved in operations, project management, business analysis, or management who needs an introduction to Data Analysis, would benefit from this class.