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Documents related to » data managers


Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. 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.

DATA MANAGERS: Six Steps to Manage Data Quality with SQL Server Integration Services Six Steps to Manage Data Quality with SQL Server Integration Services Source: Melissa Data Document Type: White Paper Description: 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
9/9/2009 2:32:00 PM

Developing a Universal Approach to Cleansing Customer and Product Data
Developing a Universal Approach to Cleansing Customer and Product Data. Find Free Proposal and Other Solutions to Define Your Acquisition In Relation To Cleansing Customer and Product Data. 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.

DATA MANAGERS: Cleansing Customer and Product Data Developing a Universal Approach to Cleansing Customer and Product Data Source: SAP Document Type: White Paper Description: 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,
6/1/2009 5:10:00 PM

Four Critical Success Factors to Cleansing Data
Four Critical Success Factors to Cleansing Data. Find Guides, Case Studies, and Other Resources Linked to 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 to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

DATA MANAGERS: Success Factors to Cleansing Data Four Critical Success Factors to Cleansing Data Source: PM ATLAS Business Group, LLC Document Type: White Paper Description: 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 to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology. Four Critical Success Factors to Cleansing Data
1/14/2006 9:29:00 AM

Data Quality: A Survival Guide for Marketing
Data Quality: a Survival Guide for Marketing. Find Free Blueprint and Other Solutions to Define Your Project In Relation To Data Quality. The success of direct marketing, measured in terms of qualified leads that generate sales, depends on accurately identifying prospects. Ensuring data accuracy and data quality can be a big challenge if you have up to 10 million prospect records in your customer relationship management (CRM) system. How can you ensure you select the right prospects? Find out how an enterprise information management (EIM) system can help.

DATA MANAGERS: Data Quality: A Survival Guide for Marketing Data Quality: A Survival Guide for Marketing Source: SAP Document Type: White Paper Description: The success of direct marketing, measured in terms of qualified leads that generate sales, depends on accurately identifying prospects. Ensuring data accuracy and data quality can be a big challenge if you have up to 10 million prospect records in your customer relationship management (CRM) system. How can you ensure you select the right prospects? Find out how an
6/1/2009 5:02:00 PM

Data, Data Everywhere: A Special Report on Managing Information
Data, Data Everywhere: a Special Report on Managing Information. Explore data management with sap netweaver MDM. Free white paper. The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and extract useful information, is harder still. Even so, this data deluge has great potential for good—as long as consumers, companies, and governments make the right choices about when to restrict the flow of data, and when to encourage it. Find out more.

DATA MANAGERS: Data, Data Everywhere: A Special Report on Managing Information Data, Data Everywhere: A Special Report on Managing Information Source: SAP Document Type: White Paper Description: The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and extract useful information, is harder still. Even so, this data deluge has great potential for good—as long as consumers, companies, and governments make the right
5/19/2010 3:20:00 PM

Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.

DATA MANAGERS: Microsoft says OLE for Data Mining: Is it Bull? Microsoft says OLE for Data Mining: Is it Bull? M. Reed - March 28, 2000 Read Comments Event Summary REDMOND, Wash., March 7 /PRNewswire/ -- Microsoft Corp. (Nasdaq: MSFT) announced the beta release of the OLE DB for Data Mining specification, a protocol based on the SQL language, that provides software vendors and application developers with an open interface to more efficiently integrate data mining tools and capabilities into line-of-business and
3/28/2000

Captured by Data
The benefits case for enterprise asset management (EAM) has been used to justify huge sums in EAM investment. But to understand this reasoning, it is necessary to explore how asset data can be used to further the aims of maintenance.

DATA MANAGERS: Captured by Data Captured by Data Daryl Mather - August 23, 2006 Read Comments Enterprise Asset Management Systems and the Aims of Modern Maintenance Since the late 1980s, enterprise asset management (EAM) vendors throughout the world have pitched their products based partly on the ability to capture, manipulate, and analyze historical failure data. Part of the stated benefits case is often the ability to highlight the causes for poor performing assets, provide the volume and quality of information for
8/23/2006

Beware of Legacy Data - It Can Be Lethal
Legacy data can be lethal to your expensive new application – two case studies and some practical recommendations.

DATA MANAGERS: Beware of Legacy Data - It Can Be Lethal Beware of Legacy Data - It Can Be Lethal Jan Mulder - August 23, 2002 Read Comments Beware of Legacy Data It Can Be Lethal Featured Author - Jan Mulder - August 23, 2002 Introduction The term legacy is mostly used for applications. For example, according to the Foldoc dictionary, legacy is: A computer system or application program which continues to be used because of the cost of replacing or redesigning it and often despite its poor competitiveness and
8/23/2002

Data Quality Strategy: A Step-by-Step Approach
To realize the 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. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

DATA MANAGERS: Data Quality Strategy: A Step-by-Step Approach Data Quality Strategy: A Step-by-Step Approach Source: SAP Document Type: White Paper Description: To realize the 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. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP
3/16/2011 2:03:00 PM

Governance from the Ground Up: Launching Your Data Governance Initiative
Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys.

DATA MANAGERS: Ground Up: Launching Your Data Governance Initiative Governance from the Ground Up: Launching Your Data Governance Initiative Source: SAP Document Type: White Paper Description: Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right
3/21/2011 1:41:00 PM

The Fast Path to Big Data
Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

DATA MANAGERS: Fast Path to Big Data The Fast Path to Big Data Source: Wipro Technologies Document Type: White Paper Description: Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of
2/7/2013 12:55:00 AM


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