The field of Diagnostic Analytics includes the capabilities to detect abnormal conditions and to estimate root causes to those conditions. This course is focused on the “detection” aspect of diagnostic analytics and introduces Statistical Process Control (SPC) as a suitable approach for defect detection. Root cause analysis of the identified defects is beyond the scope of this course. SPC includes a set of analytical techniques that measure and detect abnormal changes in the behavior of a managed process. SPC helps managers respond to unexpected changes in critical variables and take corrective action as necessary to maintain the desired levels of product quality and process performance over time.

SPC has been successfully applied to a wide range of business, technology and production processes that all have measurable outputs. It is based on the application of statistical techniques implemented in the form of control charts used to monitor the variation of important process variables or attributes.

The reduction in variation of process behavior is critical for improving both process and product quality. Successful implementation of SPC requires management commitment to continuous process improvement over time. SPC tools provide measurement and analytical inputs to an overall Quality Management framework.

This online training course provides an introduction to the concepts, techniques and applications of SPC within the context of information management practices and processes. The theory of SPC is introduced and the design of control charts is discussed as a basis for describing how a diverse range of data and process quality management challenges can be addressed.

• Identify methods for detecting defects and abnormal conditions
• Define and describe some common process building blocks
• Describe the concepts and theory behind “statistical control”
• Describe how statistical methods can be used to measure and estimate process variation
• Identify and categorize major causes of process variation
• Describe how process variation is directly related to product quality
• Discuss the principles of control charts used to detect and generate process alarms
• Present the basic concepts of quality management initiatives and practices and how it relates to the scope of Statistical Process Control
• Describe how to apply solutions to address process, data and related quality management challenges
• Provide the context necessary to implement effective solutions

• Big Data Analytics Professionals
• Data Quality Analysts
• Data Governance Leaders
• Process Improvement Analysts
• Business Analysts
• Information Technology Professionals
• Data Warehousing Team Members
• Data Warehousing and Big Data Professionals
• Program Managers and Project Managers leading various types of Business Improvement Programs
• Functional Business Managers
• Anyone with a desire to learn how statistical concepts can be applied to improve the quality of data and information and its various management processes