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Data Integration Channel

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Data Integration refers to the organization’s inventory of data and information assets as well as the tools, strategies and philosophies by which fragmented data assets are aligned to support business goals. Data integration can pursue several strategies, including single, federated or virtual compilations of data for a given business purpose. Increasingly, businesses are striving to deliver consistent data views through master data management (MDM), which is meant to deliver a near real-time, hub-based and synchronized presentation of information to any seat or point of view in the organization. Data integration today is still heavily focused on middleware, software and management tools that connect software and data end points through connectors and adaptors. Over time, companies are migrating to the philosophy of a service-oriented architecture (SOA) that applies Web protocols and standards for self-identifying application and data end points. This transition is proceeding slowly and selectively as companies are reluctant to abandon proven systems, including mainframes and traditional messaging, which remain mission-critical to business operations.

Articles

Reality Check: The Costs of Data and Application Integration

Disparate data, duplicate data and inaccessible data are all serious problems that can cripple an enterprise

When Three-Letter Acronyms Collide

Though entry points differ, user conference provides more proof that data, process and integration cannot be siloed projects

Right-Time Information for the Real-Time Enterprise

An IT organization can enable the real-time enterprise to improve business agility by delivering accurate, consistent and timely information across the extended enterprise

Five Questions Your Integration Salesman Doesn’t Want You to Ask

This article focuses on five common questions that integration sales representatives may dance around either because of shortcomings in products or a lack of knowledge about how integration is implemented.

Essential Steps for the Integrated Enterprise Data Warehouse, Part 1

This article provides guidance to what an integrated EDW is and what design elements are needed to achieve integration.

Columns

Data Integration Will Break Out of the Silo: BI and DW Trends, 8 for ’08

How’s this for irony? A lot of integration projects create more silos!

Don’t Stop at How, Learn Why

People involved in BI and DW projects are very familiar with terms such as facts, dimensions, attributes, surrogate keys and slowly changing dimensions. Knowing the terms is not enough.

Building the Information-Empowered Organization

Most companies have yet to unleash the power of improved information systems.

The Song Remains the Same

Technology and products have changed, but as I’m always reminding my consulting clients, the basis for sound data integration remains. Always remember the following basics that comprise the DIF.

Resist the Urge to Start Coding

The most important first step in designing a data warehouse/business intelligence system, paradoxically, is to stop.

Ask the Experts

What is the best approach to get an integrated view of information of both my finance and sales/production systems?

What are the best methodologies for testing data integration?

White Papers

Why and How to Build a Continuous Integration Environment for the .NET Platform

By Enterprise Solution Providers, Inc.

Informatica - Handling Variable Length Files Using XML

By Arvind Kumar

Maximize Business Value with Right-Time Information Using Data Services

By Informatica

EAI - Refine the Economics of Integration

By GaneshKumar Murugan

Profiling: Calculating Return on Investment for Data Migration and Data Integration Projects

By Informatica

Books

Enterprise Application Integration

By David Linthicum

PeopleSoft Integration Tools

By Stewart S. Miller

Common Warehouse Metamodel: An Introduction to the Standard for Data Warehouse Integration

By Dan Chang, Douglas Tolbert, David Mellor, W. H. Inmon




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