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Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

data quality problems  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration i Read More...
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Documents related to » data quality problems


The Hidden Role of Data Quality in E-Commerce Success
Successful e-commerce relies on intelligible, trustworthy content. To achieve this, companies need a complete solution at their back- and front-ends, so they

data quality problems  Hidden Role of Data Quality in E-Commerce Success Introduction E-commerce holds the promise of working seamlessly with customers, prospects, suppliers, and partners. That's why companies publish volumes of information on e-commerce sites and even open internal systems to business affiliates. Exchanging information online increases the opportunities for more sales, faster product development and fulfillment, and better relationships. Or does it? E-commerce also opens the door to data quality issues that Read More...
Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics
No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data quality can destroy its utility and

data quality problems  Data Quality Management: The Cornerstone of Zero-Latency Business Analytics The Cost Of Poor Quality Data No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data quality can destroy its utility and cost real dollars. According to recent industry studies: Poor data quality costs businesses $611 billion per year in the United States alone (TDWI). 75% of businesses have experienced significant problems due to faulty data (PWC). Only 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

data quality problems  Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Data Quality , Data Cleansing Service , Data Inte Read More...
Business Basics: Unscrubbed Data Is Poisonous Data
Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data

data quality problems  causes, among which poor data quality is high on the list. In this case, not only was data quality seen to be a troublesome issue for implementation of a new system, it was apparent that it was at the root of the material management problems that had been plaguing the company for more than a year. There were several telltale operational symptoms: 150 purchase orders and 115 change orders per month; piles of packages in the receiving department prior to their shipping date; 12 percent of the manufacturing Read More...
The Teradata Database and the Intelligent Expansion of the Data Warehouse
In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role

data quality problems  Intelligent Expansion of the Data Warehouse In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Read More...
The New Virtual Data Centre
Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business

data quality problems  New Virtual Data Centre Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward. Read More...
Managing the Tidal Wave of Data
Despite the slowing economy, data growth continues due to the digitization of infrastructures, the need to keep more copies of data for longer periods, and the

data quality problems  the Tidal Wave of Data Despite the slowing economy, data growth continues due to the digitization of infrastructures, the need to keep more copies of data for longer periods, and the rapid increase in distributed data sources. This data growth creates a wide range of management challenges. Discover solutions that can help your company maximize its storage environment and reduce costs while improving service and managing risks. Read More...
Securing Data in the Cloud
When considering adopting cloud computing or software-as-a-service (SaaS), a question most potential customers ask vendors is “How secure will our data be in

data quality problems  Data in the Cloud When considering adopting cloud computing or software-as-a-service (SaaS), a question most potential customers ask vendors is “How secure will our data be in your hands?” Customers are right to ask this question and should closely examine any vendor’s security credentials as part of their cloud/SaaS evaluations. This document is intended to give a broad overview of one vendor’s security policies, processes, and practices. Read More...
The Value of Big Data
As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity

data quality problems  Value of Big Data As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value. Read More...
Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

data quality problems  Masking: Strengthening Data Privacy and Security Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you. Read More...
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

data quality problems  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses Read More...
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