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Enterprise Data Quality

Business Driver
Poor data quality costs companies a lot of money every year. Defective data leads to breakdowns in poor business decisions, and inferior customer relationship management. Since data is a core asset of companies and needs to be managed effectively if an organizations are to generate a return from it. To many organizations, providing the infrastructure to maintain high-quality data in house is a requirement so that business driven benefits can be achieved, including:
Cost savings
Better decision-making
Improved customer service
More streamlined supply chain management

The Challenge
Most organizations that have attempted to tackle data quality have implemented tactical solutions to improve quality within a single application or within a single business process. While this approach may reduce the problem for part of the organization in the short term, such limited initiatives generally fail to achieve long-term data quality improvement on a broad scale.

The Solution
PIMA Systems in collaboration with Informatica, with  its own Data Quality Management Process provides a comprehensive, holistic approach to dealing with data quality issues. This process helps organizations continually improve data quality enterprise-wide

Enterprise Data Warehousing

Enterprise Architecture

Enterprise Data Integration   

Master Data Management

  Business Analytical Models


Best Practices
Data Warehouse and Decision Support Systems

Best Practices
Data Warehouse and Decision Support Systems

Best Practices
Data Warehouse and Decision Support Systems

The Industry Beat
Data Integration using Informatica - Video