Ibm netezza online training course - Hyderabad

IBM NETEZZA ONLINE TRAINING
Course Overview:- Netezza designs and markets high-performance data warehouse appliances and
advanced analytics applications for uses including enterprise data warehousing,
business intelligence, predictive analytics and business continuity planning.
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.
Netezza is widely credited for either inventing or bringing renewed attention to the
data warehouse appliance category, depending upon whether one regards long-time
data warehouse technology vendor Teradata as having been in the data warehouse
appliance category all along.
Introduction:
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.
Cource content:-
 Introductions and course overview
Overview of IBM Netezza architecture
Connnecting of Netezza
Getting started with IBM Netezza Analytics
Data exploration
Data Objects
Data Distribution
Data mining with IBM Netezza Analytics: Unsupervised learning methods
Data mining with IBM Netezza Analytics: Supervised learning methods
Manipulating large matrices
User-defined analytical processes