IBM Netezza Training

Introduction
IBM Netezza Analytics provides a game-changing experience for Data Scientists by allowing data miners and quantitative analysts to use all the data while still achieving high performance throughout the entire modeling cycle: from data preparation through exploratory data analysis through to model scoring and deployment.

By taking advantage of the massively parallel processing architecture of an IBM Netezza Appliance, analytics can be performed in-database so that there is no superfluous data movement. This harnesses the full power of IBM Netezza Appliance and allows data miners and quantitative analysts to greatly reduce the time to build and deploy or score a model in a single environment while using increasing massive data sets and shrinking the time from model concept to deployment

This course focuses on how to effectively exploit the IBM Netezza Analytics platform to build, test, and score analytic models in-database. Participants in this course learn how to use:

In-Database Analytics fully scalable and parallelized
In-database analytics package
R, the open source statistical language, that runs on Netezza
Matrix Engine, a parallelized, linear algebra package.
AUDIENCE
This advanced course is for analytic modelers, including data miners, quantitative analysts, and statisticians.

PREREQUISITES
You should have the following background:

Basic understanding of using advanced analytics (statistics, data mining, and so on) in business problem solutions
Working knowledge of R, SQL, or both
Working knowledge of Unix or Linux
Experience with Shell Scripting
Experience with VI Editing
OBJECTIVES
Understand how the IBM Netezza architecture and parallel processing capabilities supports modeling and analysis paradigms on large-scale data sets
Understand data mining methods in the context of use cases to solve common business problems
Apply new approaches to modeling and analysis made possible by IBM Netezza Analytics
Use Netezza Analytics data mining methods and statistical functions using the R client, or IBM Netezza
SQL (NZSQL), or both

IBM NETEZZA Training Concepts :

1.Introductions and course overview

2.Overview of IBM Netezza architecture

3.Connnecting of Netezza

4.Getting started with IBM Netezza Analytics

5.Data exploration

6.Data Obhects

7.Data Distribution

8.Data mining with IBM Netezza Analytics: Unsupervised learning methods

9.Data mining with IBM Netezza Analytics: Supervised learning methods

10.Manipulating large matrices

11.User-defined analytical processes

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