Sections include The State of Enterprise Data Quality, Data Quality Defined, The Causes of Poor Data Quality, Modeling Cures for Data Quality Assurance, Modeling for Data Entry, Accepting External Source Data, Modeling Master Data Management and Data Integration and Cleaning Up to Get Started.
Consulting is a personal relationship. You do not want to compound the fact (and it is a fact) that a client’s problems are usually people problems and not technical ones. The consulting you aspire to means you must deal with the people issues behind the complex problems at a client. Though brought in under the guise of implementing a technical solution to solve a problem, I have seldom seen real problems be caused by technology. Technical implementations, if they go well, will undoubtedly gloss over corporate problems for a while,but the corporate problems will return. Attending to the post-implementation client roles and responsibilities for success is part of true consulting.
Welcome to SearchDataManagement.com’s DataWarehouse Platforms Directory. This directory is designed to be a valuable resource for those getting started with research or evaluating optimized data warehouses. Inside, you’ll find basic information about vendors and the platforms they sell. Each listing is accompanied by a short description and a long description, including limited information about functionality and product use. You’ll find products for businesses of all sizes as well as products that can be deployed on-demand and on-premise. Use this list to get started with the evaluation process.
Welcome to SearchDataManagement.com’s Business Intelligence Product Directory. This directory is designed to be a valuable resource for those getting started with research or evaluating vendors in the business intelligence market. Inside, you’ll find basic information about the major vendors in the business intelligence market and the products they sell. Each listing is accompanied by a short description and a long description including limited information about functionality and product use. You’ll find products for businesses of all sizes as well as products that can be deployed on-demand and on-premise. Use this list to get started with the evaluation process.
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company as a whole. The data layer of an organization is a critical component because it is so easy to ignore the quality of that data or to make overly optimistic assumptions about its efficacy. Having data quality as a focus is a business philosophy that aligns strategy, business culture, company information, and technology in order to manage data to the benefit of the enterprise. Put simply, it is a competitive strategy. Just as our markets today expect operational excellence, rich product features, everyday low prices, high product quality, and short time-to-market, one day they will also expect data quality. In the meantime, each company has the opportunity to differentiate itself through the quality of its data. Leading companies are now defining what the marketplace data quality expectation will be.
Information management is key to business growth. It is a competitive advantage with the same merit as product knowledge and inventory availability. These once-held corporate competitive advantages are now considered tickets to entry and rather indistinguishable. Regulatory protections are largely gone, and when comparing your company’s features and functions, demo parity is the norm, especially within the larger industries.
Risky derivatives investments by major banks gone bad — really bad, as in billions of dollars bad — and unencrypted data tapes from two major U.S. financial institutions going missing while being transferred to backup centers are types of incidents which make it clear that appropriate safeguards are not in place in our enterprises.
In “Building Business Intelligence: Business Intelligence in Healthcare Today” featured in the May 2005 issue of Information Management, William McKnight stated, “Perhaps in no other industry, at any other time, was there such a need for business intelligence as there is in healthcare today.” Well, it’s two years later; and while we have moved the needle forward a little, by and large that statement remains true, only more pronounced. Some forward-thinking organizations in healthcare have seized upon the opportunity and have improved their access to clean and correct patient, provider and outcome metrics. Some have become the evidence-based culture mentioned then. But far too often, entrenched information is found in silos and conservative cultures are working against progress.