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Diagnostic Analytics Using Statistical Process Control
Diagnostic Analytics Using Statistical Process Control - on-line training class
 
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3-hour 50-min Online Course by Mark Peco
Single-user access license
Our Price: $385.00

Product Code: DQ-07-A


Course Exam [Add $80.00]

Description Course Outline Exam Details
 

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.

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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.

You will learn:
  • 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

This course is geared towards:
  • 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

Average Customer Review: 5 of 5 Total Reviews: 14 Write a review.

  0 of 0 people found the following review helpful:
 
Course Review July 12, 2017
Reviewer: Kazi Hasan  
Could add the speakers notes in the bottom of each slide what the speaker is talking.

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  0 of 0 people found the following review helpful:
 
Course Review February 2, 2016
Reviewer: Lourdes Villavicencio Jimenez  
I would like to include more examples related with data quality, please add examples related in a bank or a line of business.

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  0 of 0 people found the following review helpful:
 
Course Review February 2, 2016
Reviewer: Julian Eberle  
Last section was a little slow, but still valuable.

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  0 of 0 people found the following review helpful:
 
Course Review December 3, 2014
Reviewer: Wanda Diaz  
Really enjoyed this tutorial.  Clear and concise.   Two thumbs up.

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  0 of 0 people found the following review helpful:
 
Course Review October 14, 2014
Reviewer: Marut Junpueg  
Online training is great, save my time to join the class during office hour and can rerun when I want to apply to my real world.

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