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The Bottom Line on Bad Customer Data
You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for

bad data  address the impact of bad data on your company. The report gives you insight into how bad data is impacting your company and what you can do about it. How to identify where the bad data is and quantify its impact, and different approaches to determine the sources and causes of bad data are all offered in this paper. Read More
Process Manufacturing (ERP)
The simplified definition of enterprise resource planning (ERP) software is a set of applications that automate finance and human resources departments and help manufacturers handle jobs such as...
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Documents related to » bad data


Data Quality: Cost or Profit?
Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and

bad data  the probability of processing bad data increases. Ultimately, quality data is the foundation of successful CRM implementation and accurate customer intelligence. Past experience and research show that 50 to 70 percent of many CRM initiatives should be devoted to data quality. Consequently poor data quality hampers a company's ability to realize the return from their investment in a truly integrated CRM. Data quality, therefore, should not be considered a one-time exercise. It has to be integrated as a Read More
Optimizing Gross Margin over Continously Cleansed Data
Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards

bad data  shipping errors due to bad data have the potential of creating lost sales or worse - lost customers. Lost opportunity can often be directly related to bad data. Failed electronic communication projects (EDI, XML, etc), that are unable to take advantage of content feeds from data sources, vendors or customers - and the cost of employee time and effort spent cleaning up errors - can mean business opportunities lost to competition. Many industries have created standards to facilitate the exchange of Read More
Scalable Data Quality: A Seven-step Plan for Any Size Organization
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

bad data  absorb the costs of bad data quality, there is no reason why it should when, with the proper tools and a well-planned initiative, a solution is within easy reach. In a smaller organization, for which every sales lead, order or potential customer is proportionately more valuable, poor data quality is really not an option at all. If your organization survives on its ability to reach its customers, implementing a thorough data quality solution is crucial to your success. To learn more about practical and Read More
Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization
Malicious hacking and illegal access are just a few of the reasons companies lose precious corporate data every year. As the number of network security breaches

bad data  years How will the bad guys get in and what will they be targeting? A five-step plan to deploy an enterprise-wide data protection solution What should my strategy be to protect my corporate data, my customer data and my business? Twelve real-world data protection scenarios Where is data protection currently being deployed as a best practice? A three-phase deployment roadmap Where should we start; how do we secure data where it needs to be secured first and how can it evolve into an enterprise-wide data Read More
Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices
This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions

bad data  up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information Read More
Four Critical Success Factors to Cleansing Data
Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment

bad data  how you are propagating bad data through interfaces with internal systems or even worse, through EDI, XML, etc to your external customers, suppliers and vendors. Typical ERP implementations are measured on getting them completed on-time and within budget. Find an implementation including metrics of data integrity and process and you will be hard pressed. Project teams would rather perform system configuration than perform manual data review and validation. No wonder, according to Ovum Research, 50 % of da Read More
A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing

bad data  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing assoc Read More
Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a

bad data  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization's customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. Read More
The Evolution of a Real-time Data Warehouse
Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine

bad data  Evolution of a Real-time Data Warehouse The Evolution of a Real-time Data Warehouse Jorge Garcia - December 23, 2009 Understanding Real-time Systems Today, real time computing is everywhere, from customer information control systems (CICSs) to real-time data warehouse systems. Real-time systems have the ability to respond to user actions in a very short period of time. This computing behavior gives real-time systems special features such as instant interaction: users request information from the system Read More
People Don't Leave Bad Organizations. People Leave Bad Managers!
One of the most neglected areas of an enterprise is the warehouse. When errors occur here, the whole company is affected, so it is crucial that good managers

bad data  Don't Leave Bad Organizations. People Leave Bad Managers! Introduction Have you noticed that everybody and her mother is talking about how to be a good leader? Books such as Leadership Styles and Strategies, The 21 Century Supervisor , and 9 Natural Laws of Leadership are just the three of 3,048,203 search results that MSN returned when I searched leadership books. But when I searched for how to be a good follower the search engine returned 3,219 of which many were martial arts and religious Read More
Enterprise Data Management: Migration without Migraines
Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an

bad data  Data Management: Migration without Migraines Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more. Read More
Achieving a Successful Data Migration
The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data

bad data  data load will fail. Bad data in the target application can impact business processes after a go-live and necessitate costly manual fixes. Organizations must establish user confidence in the data. In order to fully trust data, business users want the ability to trace it, to find out where it came from and how it was changed. This requires some form of data lineage capability, such as metadata management. Data profiling, validation, and cleansing are also important. In application environments data quali Read More
Types of Prefabricated Modular Data Centers
Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod

bad data  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More
The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding

bad data  Necessity of Data Warehousing The Necessity of Data Warehousing M. Reed - August 2, 2000 Why the market is necessary Data warehousing is an integral part of the information age . Corporations have long known that some of the keys to their future success could be gleaned from their existing data, both current and historical. Until approximately 1990, many factors made it difficult, if not impossible, to extract this data and turn it into useful information. Some examples: Data storage peripherals such Read More

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