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Optimize the Organization’s Data Integration Practices

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As organizations process more information at faster rates, there is increased pressure for faster and more efficient data integration programs.
Data integration is an intermediary function that is critical for downstream functions of data management and business operations to be successful.
Evolving business models and uses of data are growing rapidly at rates that often exceed the investments in data management and integration tools, and as a result there is often a gap between data availability and the business’s latency demands.

Critical Insight

Identifying the right pattern for your data use cases is only part of the battle. More times than not, success in data integration is hinged on the performance of activities in development, architecture, governance, and quality.
Successful data integration solutions require more than just technology – they require design, planning, governance, and maintenance.

Impact and Result

Create a data integration program that supports the flow of data through the organization and meets the organization’s requirements around data latency.
Ensure that the necessary architecture, governance, MDM, and quality building blocks support your data integrations.
Build your data integration practice with a firm foundation in governance and reference architecture. Use best-fit reference architecture patterns and the related technology and resources to ensure that your process is scalable and sustainable.
Cloud is disrupting how traditional data integrations are performed; with new deployment methods and locations of data, new decisions around integration points and types of services must also be evaluated.
The business’s uses of data are constantly changing and evolving, and as a result the integration processes that ensure data availability must be frequently reviewed and repositioned in order to continue to grow with the business.

Published in: Data & Analytics
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Optimize the Organization’s Data Integration Practices

  1. 1. Optimize Your Data Integration Practices Ensure your organization’s data accurately flows to the critical downstream IT and business processes through effective data integration. Primary Audience: CDO, Applications Director Integrating heterogeneous data sources into one efficient and useful data warehouse that allows end users to access information easily for either operations or decision making. Data integration is the process of combining data that resides in different sources to give end users a single unified view. Pain Points: · Data is often manually assembled and reconciled from various sources for enterprise reporting · Poor data architecture documentation is increasing integration complexity and project timelines · Data is not synchronized across applications so data conflicts across systems · Duplicate records in the same source system are creating integration and reporting issues · Manually re-keying data is causing data quality issues and wasting resource time · Paying for extra application licenses so users can view key data · Performing multiple replications, cleansing, and transformation of the same data · Poor access to data residing in applications with a limited number of licenses Identifying the right pattern for your data use cases is only part of the battle. Often, success in data integration hinges on the performance of activities in development, architecture, governance, and quality rather than the integration activities themselves. Data integration is dependent on capabilities of these additional disciplines in order to be able to properly provide the necessary data to the business in a timely fashion. Empower and optimize this function of Data Management after having laid the proper foundations in other areas. · Improve your chances of success by establishing a plan: with an appropriate scope, that focuses on solving the right problems, and is aligned with the business drivers for improving data integration. · Data integration is just one component of the larger data management puzzle. In order for it be successful, core activities related to foundational data management practices must be implemented and working efficiently. · Successful data integration solutions require more than just technology – they require design, planning, governance, and maintenance.
  2. 2. http://www.infotech.com/research/ss/optimize-the-organization-s- data-integration-practices

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