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Kursbeskrivning: IBM Netezza Appliance Usage (ILO)

Kursen har inget datum. Ring vår kursbokning 077 186 10 37 för information om en privat utbildning.

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Översikt

  • Målgrupp
  • Förkunskaper
  • Mål
  • Nyckelområden
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Kurskod 3W501SE Leveranstyp Instructor Led - Online Training
(Hands-on labs)
Kurslängd 3.0 dagar Kurstyp
Listpris SEK 17 400,00 exkl moms
SEK 21 750,00 inkl moms
   

This is an online course. Please do not make travel arrangements for this course. After you receive confirmation that you are enrolled, you will be sent further instructions to access course material.

This course will teach participants database administration for the IBM Netezza 1000. This course is designed to give the participant an overview of the IBM Netezza 1000 architecture and provide a working knowledge and understanding of the Netezza database features and best practices.

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Roadmaps:

  • Netezza Appliance
  • PureData System for Analytics, powered by Netezza

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Målgrupp

This advanced-level course if for:

  • Database Administrators
  • System Administrators
  • Application Developers
  • Data Warehouse Architects

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Förkunskaper

Participants are required to have:

  • a working knowledge of UNIX or Linux, experience with shell scripting, experience with VI editing, and basic SQL

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Mål

  • Administer the IBM Netezza 1000
  • Configure client connectivity
  • Create databases and tables
  • Determine distribution methods
  • Set up Clustered Base Tables
  • Load and unload tables
  • Generate statistics
  • Analyze query plans
  • Create materialized views
  • Reclaim unused disk space
  • Program stored procedures

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Nyckelområden

  • where data warehouse appliances come from
  • IBM Netezza data warehouse architecture
  • connecting to IBM Netezza data warehouse applicance host
  • managing user access to IBM Netezza database'
  • NzAdmin
  • databases and tables
  • distribution
  • loading and unloading tables
  • ODBC / JDBC / OLE-DB client connectivity
  • optimizer and query plans
  • zone maps and cluster base tables
  • materialized views
  • statistics
  • cross-database access
  • transactions
  • reclaiming disc space using GROOM
  • processing data using stored procedures

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