ETL Channel

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Extract, transform and load (ETL) is the core process of data integration and is typically associated with data warehousing. ETL tools extract data from a chosen source(s), transform it into new formats according to business rules, and then load it into target data structure(s). Managing rules and processes for the increasing diversity of data sources and high volumes of data processed that ETL must accommodate, make management, performance and cost the primary and challenges for users. The traditional ETL approach requires users to map each physical data item with a unique metadata description; newer ETL tools allow the user to create an abstraction layer of common business definitions and map all similar data items to the same definition before applying target-specific business rules, isolating business rules from data and allowing easier ETL management.

SQL Skills Essential for ETL Developers

The strength of the SQL, if used intelligently, can increase the performance and reduce complexity of ETL mappings

Advancing the Art of Data Integration

Why are so many DI users unhappy, and why is the DI industry in what Gartner calls the “trough of disillusionment” that technologies fall into when they fail to meet expectations?

Beyond ETL and Data Warehousing

Data integration suffers from an image problem - it has become synonymous with extract, transform and load

Right-Time ETL and Integration

Developments in advanced data loading and real-time integration are exciting and applicable to many business situations, but seven best practices must be applied to fully leverage the technology

Information Management: Myths and Facts

Lalitha Chikkatur identifies eight myths in information management

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The What-If Review

The technical design process should include worst-case scenario planning

Back to the Basics of Data Warehousing

Approaches, methods and techniques from the early days of data warehousing are still applicable today

Technology Components of a Scalable Architecture

All of the components of a business intelligence architecture must independently scale horizontally and/or vertically or through specific functionalities

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To V or Not To V: Business Intelligence Gets Virtual

Evaluating Real-Time Data Integration Solutions

Advanced ETL with Pentaho Data Integration

By Christopher Lavigne

Third Generation ETL: Delivering the Best Performance

By Yves De Montcheuil and Chris Dupupet

Sunopsis Integration Suite: An Evaluation by Bloor Research

By Bloor Research

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Building and Managing the Meta Data Repository: A Full Life-Cycle Guide

By David Marco

Managing Gigabytes: Compressing and Indexing Documents and Images

By Ian H. Witten, Alistair Moffat, Timothy C. Bell

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• Product Overview: Time to simplify data integration?
  Expressor software is redefining data integration with an innovative technology that is smarter, faster and more affordable than current technology.
• White Paper: Data Integration: What’s Next?
  Today’s DI tools claim to offer significant benefits however there can be many challenges and constraints.
• Primer: Netezza and expressor
  The expressor data loader for Netezza is designed to integrate the system with the NPS appliance.

• Find ETL products & services on Information Management Marketplace

Articles from this Site

• Syncsort and Vertica Break Database ETL World Record
• Technology Components of a Scalable Architecture
• From Business Process Management to Business Process Intelligence: The Road to the Predictive Enterprise
• With respect to ETL integration from one system to the other, what steps needs to be considered when planning an aquisition or merger?
• Data is at the Heart of Enterprise-Wide BI and DW, Part 4
• More Articles from this Site

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White Papers

• To V or Not To V: Business Intelligence Gets Virtual
• Evaluating Real-Time Data Integration Solutions
• Third Generation ETL: Delivering the Best Performance
• Sunopsis Integration Suite: An Evaluation by Bloor Research
• Advanced ETL with Pentaho Data Integration
• More White Papers

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Books

• Building and Managing the Meta Data Repository: A Full Life-Cycle Guide
• Managing Gigabytes: Compressing and Indexing Documents and Images
• More Books