Documents » nursing quality assurance reports.
Abstract: Today’s mobile software companies face a daunting challenge: How can they achieve
quality while getting to market swiftly? After all, speed is king in the mobile market. The trade-off between speed and
quality in mobile software development is an illusion—or should be. Get a closer look at the situation with a framework that presents a way to use
quality assurance (QA) processes to accelerate development.
PubDate: 10/20/2009 8:01:00 AM
Abstract: At a time when many companies are concerned about operational expenditure, a business assurance system with consultancy can help. Instead of randomly entering a remediation program whenever a major fault is found, use the business assurance system. The following areas have seen results: revenue management, customer acquisition and retention, credit management and bad debt recovery, supply chain management, among others.
Abstract: In today’s world, current and future customers are interested to know whether or not you have implemented a quality control system. Some customers will demand International Organization for Standards (ISO) certification, and others may just ask about it. Whatever their requirements, having a quality control system assures your customers that the products and services you offer are of high quality.
Abstract: Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.
Abstract: When your quality control plan is complex because there are many features to control—and it involves many people—you need to pay special attention to your quality control process. Also, a complex plan places high demands on your software solution. Discover how an online integrated factory information system can work across production, job tracking, spoilage, and quality to support all of your quality control processes.
Abstract: Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.
Abstract: Quality does not start at the receiving dock and end at the shipping dock. The focus on the supply chain demands that the quality department be involved from the beginning to the end of the supply chain.
Abstract: In today’s global market, providing quality products and services is essential for any manufacturer’s continued growth—but maintaining a competitive edge is not always easy. For success, quality awareness must begin at the conception of the product and continue throughout the various stages of its development. To improve in this area, many manufacturers are now adopting the total quality management (TQM) approach.
Abstract: 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.
Abstract: Data quality sounds like a motherhood and apple pie issue, of course we want our data to be right. However, very few enterprises get serious about it. Maybe that's because the cost of data quality is hidden. That cost can be huge.
Abstract: As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.
Abstract: Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.
Abstract: Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue.
Abstract: Learn how Cubic Defense Systems improved their overall product quality and government compliance, while conforming to support mission-critical processes by using Cincom's integrated quality management solution.
Abstract: To realize the full benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it, and how to keep it clean. The companies that approach this issue strategically are the companies that will be successful. Learn the six factors that go into a good data quality strategy, and find out how to go from strategy to implementation.
Abstract: Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.
Abstract: 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.
Abstract: Organizations are beginning to wake up to the fact that the data they collect and manage should be viewed as a corporate asset. Data is the one thing that separates you from your competitors—and the quality of your data can be your competitive advantage or disadvantage. Discover six key steps you can take and put into effect to help you realize a tangible return on investment (ROI) on your data quality initiative.
Abstract: Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.