Data Scrubbing

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Results 1 - 9 of about 9 for Data Scrubbing Search took 0.12 seconds.

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Data Quality: Cost or Profit?

by Kevin Ramesan

... Data scrubbing is the process of fixing or eliminating individual pieces of data
that are incorrect, incomplete or duplicated before the data is passed to a ...

http:/.../Research/ResearchHighlights/Crm/2004/03/research_notes/MI_CR_KR_03_08_04_1.asp - 14k - 2004-03-08

Summary: Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negat

A Definition of Data Warehousing

by M. Reed

... others to match the rule. This process is also referred to as "data scrubbing"
or "data quality assurance". It can be an extremely ...

http:/.../Research/ResearchHighlights/DataWarehousing/2002/08/research_notes/TU_DW_MFR_08_18_02_1.asp - 15k - 2002-08-18

Summary: 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 describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an ext

N-Tier Demand Management

by Bill McBeath

... This data is factored into the forecasting scrubbing process to eliminate duplicate
demand (see sidebar "Rationalizing Demand Across Channels"). ...

http:/.../Research/ResearchHighlights/Scm/2004/12/research_notes/TN_SC_XBM_12_23_04_1.asp - 13k - 2004-12-23

Summary: The classic bull-whip effect means that the further a supplier is removed from the end consumer, the worse are the fluctuations in demand that they see. This has led many to recommend an n-tier approach to demand management, where everyone gets visibility to the end-customer demand at the same time. In p

SCM System/SCM Software Comparison and Evaluation

... support DDE DES data Data Integration Technologies Data Management Options Data
cleansing and normalization (scrubbing, mapping, and aliasing) Data cleansing ...

http://scm.technologyevaluation.com/supply-chain-optimization// - 71k - 2009-03-09

SCM System/SCM Software Comparison and Evaluation

... Data capture refers to capturing information contained in a bar code or RFID Data
cleansing and normalization (scrubbing, mapping, and aliasing) Data cleansing ...

http://scm.technologyevaluation.com/ - 101k - 2009-03-09

Compare CRM (Financial/Insurance Market) Software

... channels Java Manages incoming e-mails from customers with automatic guided-through
questionnaires and outbound e-mails combined with customer's data. ...

http://crm.technologyevaluation.com/financial-insurance/ - 101k - 2009-04-21

Summary: Compare CRM software: Discover the 10 key modules to base your selection on and tools you must use in order to save up to 85% of time and money you'd spend gathering information on your own : Insurance and Investment , Marketing Automation, Sales Force Automation (SFA), CRM Analytics, Call Center and Cu

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Data Scrubbing

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1.	A Definition of Data Warehousing (6 Pages) by M. Reed Aug 18, 2002 Abstract : 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 describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
2.	A Definition of Data Warehousing (6 Pages) by M. Reed Aug 24, 2000 Abstract : 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 describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
3.	Data Quality: Cost or Profit? (4 Pages) by Kevin Ramesan Mar 8, 2004 Abstract : Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.
4.	Business Basics: Unscrubbed Data Is Poisonous Data (4 Pages) by J. Dowling Nov 26, 2003 Abstract : 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 quality is low, and the short- and long-term benefits are great.
5.	A CRM System Needs A Data Strategy (7 Pages) by David McNamara Jul 3, 2003 Abstract : A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact with customers and prospects. Collecting data, however, cannot be isolated from a strategy for actually using that data. Here is an overview of how to evolve the focus of a data strategy to specifically suit both the acquisition and retention phases.
6.	Business Basics: Unscrubbed Data Is Poisonous Data (4 Pages) by J. Dowling Jun 13, 2001 Abstract : 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 quality is low, and the short- and long-term benefits are great.
7.	A CRM System Needs A Data Strategy (7 Pages) by David McNamara Jan 18, 2001 Abstract : A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact with customers and prospects. Collecting data, however, cannot be isolated from a strategy for actually using that data. Here is an overview of how to evolve the focus of a data strategy to specifically suit both the acquisition and retention phases.
8.	A CRM System Needs A Data Strategy (7 Pages) by David McNamara Jan 3, 2001 Abstract : A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact with customers and prospects. Collecting data, however, cannot be isolated from a strategy for actually using that data. Here is an overview of how to evolve the focus of a data strategy to specifically suit both the acquisition and retention phases.
9.	Data Mining: The Brains Behind eCRM (6 Pages) by Steve McVey Nov 6, 2000 Abstract : Data mining has emerged from obscure beginnings in artificial intelligence to become a viable and increasingly popular tool for putting data to work. Data mining is a set of techniques for automating the exploration of data and uncovering hidden truths.

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