Good data quality leads to better business outcomes

Data quality improvement is not a new concept, in fact it has been around for a long time. In general, the goal of cleaning, standardizing and enriching enterprise data with data quality processes has not changed. The only difference is that at present, under the premise of intensifying market competition and economic downturn, a sound enterprise data quality management model can completely distance the gap between leaders and laggards. Having a solid business data quality management model can help your business more fully enjoy the benefits of turning your business data into key strategic assets.

This means increasing revenue, cutting costs and reducing risk. By adopting the right solution, organizations can get around the data quality issues as they arise, making the most of their data in ways never seen before. Doing so ensures that key IT businesses-business intelligence, master data management, and enterprise applications-deliver better business results. In particular, business applications are the lifeblood of business organizations. Enterprise applications are designed to automate key business processes and they determine the smooth execution of key business processes. Given the indispensability of data for enterprise applications, the performance of enterprise applications is directly affected by the quality of the data being processed. However, surprisingly, this relationship is often overlooked. Application managers and enterprise architects usually only emphasize how to better maintain and enhance their enterprise application portfolio, but did not synchronize attention to improve data quality. If things go on like this, they will fall into the quagmire of being able to cope with the low performance of applications, and they will delay the demand for data quality. A recent study by Ovum, an independent research firm, entitled "Optimizing Enterprise Applications: Data Connectivity," points out that data sprawl and poor quality data are the culprits behind poor application management and performance, pointing to poor data and implementation or operational applications The original intention of the program runs counter to. "Regardless of how well the application platform is structured or the efficiency of the development team, all efforts to improve application management and delivery will be futile in the face of weaknesses in underlying data and its management policies." Ovum surveyed senior IT executives from 146 large enterprises located in North America, Australia and the United Kingdom. The survey results show that the main reason for the impact of application sustainability lies in data issues. These issues include: App Delivery - Delivering clean, credible data, compliance and timely access are among the top challenges. Application Performance - Performance issues plague nearly 85% of companies surveyed for lack of standardized data, inefficient (or lack of) filing policies and, secondly, excessive peer-to-peer interface. Application data management - data reliability involves all applications, an average of 20% to 30% of the data is repeated. This has led to a sustained increase in application maintenance costs. In addition, issues related to data migration, synchronization and retention are also tops. Successful companies often leverage data analytics and data quality solutions to help them maximize the return on their application investment. These flexible, yet comprehensive solutions help organizations reduce the complexity and cost of application maintenance by tracking the discovery of complex anomalies in enterprise data, enabling real-time data quality improvements during data entry or large-scale data transfers. Such as ACH Foods, a grocery and foodservice business that sells specialty concentrated products and oil-based dairy products, cheese-free spray-dried products and cheese, spray-dried appetizers and ingredients series, A number of leading cereal brands on the market. Faced with the ever-increasing complexity of the application environment, the company enhanced its operational efficiency by deploying enterprise ERP solutions. In the meantime, it attached great importance to data quality and made a simultaneous commitment to data quality solutions. As a result, the company significantly improved its new applications The efficiency of the project from input to efficiency and accelerate the return on investment. Informatica's data quality solution, Informatica Data Quality, delivers a single, unified platform that delivers authoritative and trusted data quality across all stakeholders, all projects, and across all data domains (on-premise or in the cloud) for all projects and business applications. Informatica Data Quality offers: A unified role-based tool that enables business and IT departments to collaborate around data quality processes to reduce reliance on limited IT resources Full support for all data and purposes-enabling data Quality rules apply to customers, products, finance, assets, and large data such as social media data, and are reused across all types of data integration, master data management (MDM), and data quality projects. These rules are open to all applications - You can then access any data source that resides anywhere (on premise, partner, or in the cloud) and can deploy centralized data quality rules to improve data quality across all applications With Informatica Data Quality, Enterprise Organizations can proactively monitor and clean data for all applications, keeping data clean; enable business people to share data quality and data governance responsibilities; and achieve better business outcomes with trusted enterprise data.