Part 1: Measuring Overall Quality using Robust Quality Index (RQI) Approach
Part 2: Individualized Precision Analytics using dataDragon Approach
By
Dr. Rajesh Jugulum
Part 1: Measuring Overall Quality using Robust Quality Index (RQI) Approach
The term quality should be expanded as a measure of process, data and analytics. Quality should be measured with a holistic approach by Robust Quality. This workshop will focus on establishing these relationships and explains how robust quality index (RQI) can be used to measure overall quality. Increase in RQI indicates improvements in both data and process quality in the system. The RQI approach, to large extent, intended to minimize the loss to society that is improving quality levels as defined by Dr. Genichi Taguchi.
Part 2: Individualized Precision Analytics using dataDragon Approach
dataDragon analytics platform aims at providing unique individualized insights by analyzing large volumes of data with multiple variables through the use of statistical and process methods. Further the platform focuses on moving away from population based models/analytics individuals by way of constructing a multivariate measurement scale with ability of measure degree of abnormality (separation) from desired group of individuals. In this part of the workshop we will focus on dataDragon approach with several case examples. Besides a demo of this approach will also be made.