Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace. The IBM InfoSphere Big Match on Hadoop course will introduce students to the Probabilistic Matching Engine (PME) and how it can be used to resolve and discover entities across multiple data sets in Hadoop.
Students will learn the basics of a PME algorithm including data model configuration, standardization, comparison and bucketing functions, weight generation, and threshold.
During the exercises, the student will work on a large use case, where they will apply their knowledge of Big Match to discover relationships be two data sets that can be used to understand the full view of the member data. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. Terms and Conditions: Ingram Micro – https://www.ingrammicrotraining.com/Terms-of-use.aspx; IBM – http://www.ibm.com/training/terms

Version:

v11.4

Audience:

The course is designed for a technical audience that will be setting up a custom algorithm for the Probabilistic Matching Engine to use Big Match on Apache Hadoop to compare, match and/or search member records across multiple data sets.

Objectives:

Detail:

Pre-Requisites:

This course has no pre-requisites.