The Importance of a Single Product for Data Quality and Data Integration

  • Source: BI Research
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Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data.

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11 Criteria for Selecting the Best ERP System Replacement

An enterprise resource planning (ERP) system is your information backbone, reaching into all areas of your business and value chain. That’s why replacing it can open unlimited business opportunities. The cornerstone of this effort is finding the right partner. And since your long-term business strategy will shape your selection, it’s critical that your ERP provider be part of your vision. Read More

Product Analysis Report: IBM Cognos and SPSS Solutions

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  • Written By: Jorge Garcia
  • Published: December 17 2013
Many organizations today have come to realize that using data effectively should be a key component of their business strategy. Businesses can expand and improve the information analysis capabilities gained through BI by using predictive analytics to anticipate risks and outcomes, predict trends, and discover unseen patterns in data. IBM SPSS solutions provide a complete set of predictive analytics capabilities and a flexible set of integration points with Cognos Business Intelligence. Read the report to learn more about how IBM Cognos software capabilities can be extended with the use of IBM SPSS predictive analytics capabilities. Read More

Manufacturing Cloud: Moving Toward a Single Source of Truth in the F&B Industry

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Six Steps to Manage Data Quality with SQL Server Integration Services

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The Importance of a Single Platform for Data Integration and Quality Management

Rising data volume is not the only reason companies are concerned with issues of data integration and data quality. The growing numbers of disparate systems that produce and distribute data add to the complexity. But in many companies, data quality management has not kept pace with the growth of data integration projects, and its use is immature. Find out how moving toward a single data services architecture can help. Read More

Developing a Universal Approach to Cleansing Customer and Product Data

  • Source: SAP
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