Data Quality

Sound data quality is a fundamental requirement of successful data management programs. However, the importance of data quality may be overlooked by executives who take it for granted. This e-book provides readers with advice designed to help them win approval for data quality initiatives on both IT and business grounds.

Sound data quality is a fundamental requirement of successful data management programs, and problems with data...

gain approval for implementing a program to increase your data quality. Also find information on how to best assess and manage your data, as well as evaluating whether or not data quality software is right for you.

Despite its impact on your overall business performance, many organizations overlook the importance of high quality data. But improving and maintaining data quality comes at a high financial cost and making a case for a data quality improvement program isn’t always easy.

Read this...

45;quality data foundation, but companies often neglect data quality until a major problem occurs that could've been avoided. Learn about the benefits and importance of da... Most manufacturers would never think of eliminating the quality control function from their production processes. Without quality control, the number of defective products that must be reworked, scrapped or returned would dramatically increase. Yet ensuring data quality within operational and business...

evident that effective predictive models begin with data quality management. Read on to learn more about the impact data quality has on predictive analytics and how to easily improve your data quality.

In today’s business world, most enterprises are on a mission to find innovative ways to enhance their business intelligence strategies, and forward-thinking companies have zeroed in on the capabilities of predictive analytics. 

But, as their popularity grows it’s becoming evident that...

on enterprise data issues. This discussion is about data quality and some of the challenges and pitfalls that are seen during data quality implementation.

This presentation transcript features speaker Evan Levy, partner and co-founder of Baseline Consulting, a professional services firm concentrating on enterprise data issues.

This discussion is about data quality and some of the challenges and pitfalls that are seen during data quality implementation. Evan will discuss data...

e-guide and learn about the serious financial costs poor data quality can have on your organisation. Uncover the importance of data quality and increase your overall economic competitiveness.

Data quality is becoming increasingly important to the success of today’s organisations. As the use of business intelligence (BI) systems and data analytics tools becomes more pervasive, companies are demanding high-quality data to help executives and other users make vital business decisions...

management market. The software unifies our leading data-quality and integration solutions - helping your organization to move, transform, and improve virtually any type of data anywhere, at any frequency.

In today's world of huge data volumes and multiple, disparate data sources, business users often are challenged to harness and make sense out of chaos. As organizations grow both organically and through mergers and acquisition, these problems keep mounting. Exponential growth in...

involved with a major initiative such as MDM, BI, or CRM- and data quality or data governance seemed to be just an afterthought? It becomes clear to you that data quality was never included in the project in the first place. Or have you implemented data quality solutions at a project layer, only to ignore those upstream and downstream interdependencies of data quality?

 If you don't get the data quality right at the outset of the initiative, and if you don't set down rules for governing data and...

Tune in to this Webinar to find out how data quality can improve business performance. You’ll learn how to improve key data areas by performing data quality profiling and data collection through closed-loop monitoring, and how to address data quality as a process to derive value and drive continuous improvement.

Tune in to this Webinar to find out how data quality can improve business performance. You’ll learn how to improve key data areas by performing data...

you will get a side-by-side comparison of SAP and Oracle's data quality portfolios along with expert advice.

German enterprise software goliath SAP AG is well ahead of its chief rival, Oracle Corp., in the race to gain the biggest share of the data quality software market, but Oracle is catching up fast, according to the latest Gartner Magic Quadrant for Data Quality Tools.

Oracle has been ramping up its data quality portfolio through key acquisitions, while SAP, which acquired business...

This paper uncovers the importance of data quality management as it relates to predictive analytics.

Organizations of all types and sizes are enhancing their business intelligence (BI) strategies with predictive analytics. Forrester Research Inc. found that business analytics is the fastest-growing segment of global IT software, with close to 70% of companies polled expressing a strong interest.

Traditional reporting and analysis provide you with a rear-view...

makers in an enterprise to have access to the highest quality data that meets compliance standards.  This white paper introduces a data management system that provides a unified strategy for both business and IT users to plan, implement, monitor, and govern critical information.

Decision-makers that rely on the highest quality data to make critical business assessments cannot afford inaccurate information.  Especially with increases in regulatory oversight, it is essential now...

in the Leaders Quadrant of its 2010 “Magic Quadrant for Data Quality Tools” report. Gartner’s Magic Quadrants evaluate vendors within a particular technology market based on their completeness of vision and ability to execute. Use this Magic Quadrant to understand the data quality tools market.

DataFlux was recently positioned by Gartner, Inc. in the Leaders Quadrant of its 2010 “Magic Quadrant for Data Quality Tools” report. Gartner’s Magic Quadrants evaluate...

and government organizations are learning that poor-quality data is damaging their ability to support business processes, comply with regulations and make accurate decisions.

Even though most business leaders understand the need for high-quality data, they are often not sure how to achieve it. This is where IBM InfoSphere Information Server can make a big difference. InfoSphere Information Server is the foundation of many successful data quality initiatives, helping...

With SAP Data Quality Experts, enthusiasts and Project Managers in mind, this paper is written specifically for companies interested in understanding how to best approach and plan for maintaining sustainable business-ready data in SAP. It discusses five key questions as a baseline from which an organization can begin planning for a data... With SAP Data Quality Experts, enthusiasts and Project Managers in mind, this paper is written...

Learn about the importance of having a data quality strategy and setting the overall goals. The six factors of data are also explained in detail and how to tie it together for implementation.

Learn about the importance of having a data quality strategy and setting the overall goals. The six factors of data are also explained in detail and how to tie it together for implementation.

resolution complements and extends the application of data quality and data integration processes into business applications. The market for Identity Resolution processes has evolved from simple search and match functionality for customer service, fraud detection, and security screening processes to today's highly accurate, high-performance, real-time, cross-language search and match services across multiple application. This paper describes how...

Group 1 Software presents a case study in enterprise data quality success featuring the DaimlerChrysler Corporation, a leader in the automotive manufacturing industry. DaimlerChrysler relies on its customer database to enhance marketing effectiveness, and reduce operational costs. In this ongoing pursuit of quality, DaimlerChrysler needed to consolidate their multiple operational databases into one set of data stores to join disparate data and achieve an accurate...

Tune in to this Webinar to find out how data quality influences the effectiveness of predictive analytics and forecasting. You’ll learn how to go beyond name and address matching to realize the potential of numerical data quality, how to overcome insufficient yet relevant data from your predictive and forecasting models, and more.

Tune in to this Webinar to find out how data quality influences the effectiveness of predictive analytics and forecasting. You’...

and compare multiple data sources simultaneously through data quality and data integration workflows. Although decision-making was decentralized throughout the company, the bank's corporate headquarters still needed to create credit risk management reports that would allow those local decisions to be consistent with corporate goals and objectives for the entire company. This would ensure that executives at the bank's 50 units would have the information they needed to...

whether our business rules are consistently applied.

Data quality is the usual suspect, but equally, we should also question the effectiveness of our data integration in data warehouses and marts. It is difficult to achieve total integrity when the business rules used for derived data are spread across multiple ETL strings as on-the-fly transformations or applied as last minute transformations in the fragmented BI components.

IT has rightly turned to enterprise data warehouses and...

by many organizations for their data integration and data quality projects. These organizations span all industries, all continents, and all company sizes. More importantly, their projects range from ETL for business intelligence to operational data, data quality, master data management, etc.

This third volume of Practical Open Source Data Integration: Case Studies & Implementation Examples presents selected case studies, illustrating real-life implementations of open source...

Webinar to find out how to improve key data areas through data quality profiling and provide decision makers with trustworthy information. You’ll learn how to apply analytics to your reliable, high-quality data and come away with insights that optimize your organization’s decision-making capabilities.

Tune in to this Webinar to find out how to improve key data areas through data quality profiling and provide decision makers with trustworthy information. You’ll learn how...

technology can have when that technology addresses data quality, usability, and intelligence.

In this study of over 150 Fortune 1000 firms from every major industry or vertical, the University of Texas explored issues associated entirely with the lifeblood of today’s enterprises: data. The quality of data, the ability for that data to be accessed wherever and whenever it’s needed, and the relevance of that data in addressing a specific problem.

The findings definitely demonstrate the...

SAP success. If your organization hasn't considered data quality, it's strongly recommend you reconsider. In most cases, the costs of implementing a holistic data-governance solution greatly outweighs the risks involved with not having any governance. Implementing a data-governance strategy is essential for sustainable SAP success. If your organization has not yet considered data quality on its critical path to SAP success, it's strongly recommend you reconsider. In most cases, the...