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Data quality drives enforcement of business standards and rules across the enterprise
Each year, organizations collect volumes of data - across databases and applications - about their customers, products, suppliers, employees, finances and inventory. The result is a fractured, confused view of the enterprise that affects customer relationships, supply chain initiatives, and virtually every key business decision.
The explosion in the sheer amount of data is leading companies to explore data governance initiatives. Data governance involves the people, processes and technologies required to enforce corporate data standards. And at the core of any data governance initiative is data quality.
Data quality technology provides the ability to automate the processes of establishing a unified standard for data. Through business rules monitoring, companies can establish a "check" against bad or non-conforming data - and provide alerts when information does not meet pre-set standards. The technology can also enforce data quality rules in real time to eliminate poor data at the source.
As data governance initiatives expand, companies need a solution designed to propagate business standards across the IT and business environments. For example, data originating in a CRM system should utilize the same rules as your data warehouse, ERP system or call center application. By creating a standard for data quality - across business units or divisions - you can lay the groundwork for a more unified enterprise. And build the foundation for a more successful, competitive organization.
Data knows no geographic boundaries
The globalization of business is driving companies to think more strategically about their data. Organizations often store, manage and share corporate information across different regions, languages and cultures. As the data spreads, corporate data governance can help mitigate the problems that occur with the inevitable data differences between regions.
To allow an organization to fully understand its business around the globe, you need a data quality integration solution capable of improving and consolidating data from every continent. A solution that can be configured to meet specific regional and language demands. A solution capable of driving a single, unified view of the enterprise worldwide.