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Documents related to » conditional and mathematic data transformations


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.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: Four Critical 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
1/14/2006 9:29:00 AM

Understanding the PCI Data Security Standard
Understanding the PCI Data Security Standard.Secure Documents and Other Computer Software to Use In Your Complex System of Understanding the PCI Data Security Standard. The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a proactive rather than passive way. These include security management, policies, procedures, network architectures, software design, and other protective measures. Get a better understanding of the PCC DSS and learn the costs and benefits of compliance.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: Understanding the PCI Data Security Standard Understanding the PCI Data Security Standard Source: Symantec Document Type: White Paper Description: The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a proactive rather than passive way. These include security management, policies, procedures, network architectures, software design, and other protective measures. Get a better understanding of the PCC
9/3/2009 4:36:00 PM

Optimizing Gross Margin over Continously Cleansed Data
Optimizing Gross Margin over Continously Cleansed Data.Reports and Other Software System to Use In Your System for 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 are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of product information is accurate and synchronized, internally and externally.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: Optimizing Gross Margin over Continously Cleansed Data Optimizing Gross Margin over Continously Cleansed Data Source: epaCUBE Document Type: White Paper Description: Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards are automated data cleansing, systematic management of data processes, and margin optimization. Real dollars can be reclaimed in the supply chain by making certain that every byte of
6/20/2006 9:23:00 AM

Scalable Data Quality: A Seven-step Plan for Any Size Organization
Scalable Data Quality: a Seven-step Plan for Any Size Organization. Read IT Reports In Relation To Data Quality. 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 it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: Scalable Data Quality: A Seven-step Plan for Any Size Organization Scalable Data Quality: A Seven-step Plan for Any Size Organization Source: Melissa Data Document Type: White Paper Description: 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 it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor
9/9/2009 2:36:00 PM

The Path to Healthy Data Governance through Data Security
Companies today are challenged to maintain their data safe and secure from hackers and others with unauthorized access. In his article, TEC business intelligence (BI) analyst Jorge García looks the risks and issues that companies face with securing their data, the importance and advantages of data security, and outlines a path that companies can follow to achieve data security as part of an overall data governance initiative.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: The Path to Healthy Data Governance through Data Security The Path to Healthy Data Governance through Data Security Jorge García - April 24, 2012 Read Comments The appropriate handling of an organization’s data is critically dependent on a number of factors, including data quality, which I covered in one of my earlier posts this year. Another important aspect of data governance regards the managing of data from a security perspective. Now more than ever, securing information is crucial for any
4/24/2012 2:48:00 PM

Metagenix Reverse Engineers Data Into Information
Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: Metagenix Reverse Engineers Data Into Information Metagenix Reverse Engineers Data Into Information M. Reed - February 15, 2001 Read Comments M. Reed - February 15, 2001 Event Summary Metagenix, Inc. has designed its flagship product, MetaRecon to, as they put it, Decipher Your Data Genome . The product reverse engineers all of the metadata ( data about data ) from data sources and generates information that is very helpful to developers in designing specifications for a new data store, and assists
2/15/2001

Data Mart Consolidation and Business Intelligence Standardization
Improve data mart and business intelligence (BI) consolidation with Teradata and SAP BusinessObjects platforms.Download free white papers! Making information broadly and easily available to more users throughout an organization—and beyond the organization to customers, partners, and stakeholders—has never been more imperative. More enterprises are coming to understand the value of placing consistent, integrated data into the hands of everyone who needs it. Learn how a data mart consolidation program can help you improve decision making while cutting costs.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: Data Mart Consolidation and Business Intelligence Standardization Data Mart Consolidation and Business Intelligence Standardization Source: SAP Document Type: White Paper Description: Making information broadly and easily available to more users throughout an organization—and beyond the organization to customers, partners, and stakeholders—has never been more imperative. More enterprises are coming to understand the value of placing consistent, integrated data into the hands of everyone who needs it.
3/2/2010 10:32:00 AM

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.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: 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

Infor s Big Data Cloud in the Sky » The TEC Blog
Infor s Big Data Cloud in the Sky » The TEC Blog TEC Blog     TEC Home     About TEC     Contact Us     About the Bloggers     Follow TEC on Twitter    RSS   Discussing Enterprise Software and Selection --> Fast, Accurate Software Evaluations TEC helps enterprises evaluate and select software solutions that meet their exacting needs by empowering purchasers with the tools, research, and expertise to make an ideal decision. Your software selection starts here. Learn more about TEC s

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: amazon redshift, bi, big data, Cloud, ERP, industry watch, infor, infor 10x, infor ion, infor mingle, infor sky vault, inforum 2013, sap hana, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
02-05-2013

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.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: 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

EMC to Buy Data General
WALTHAM, Mass., August 9th, 1999 (Reuters) - High-end data storage leader EMC Corp. (NYSE:EMC) on Monday moved to grab a chunk of the mid-range storage business with a deal to buy Data General Corp. (NYSE:DGN) for $1.1 billion in stock, the companies said.

CONDITIONAL AND MATHEMATIC DATA TRANSFORMATIONS: EMC to Buy Data General EMC to Buy Data General R. Krause - August 13, 1999 Read Comments EMC to Buy Data General WALTHAM, Mass., August 9th, 1999 (Reuters) High-end data storage leader EMC Corp. (NYSE:EMC) on Monday moved to grab a chunk of the mid-range storage business with a deal to buy Data General Corp. (NYSE:DGN) for $1.1 billion in stock, the companies said. EMC, which holds a 35 percent share of the $12 billion high-end storage market, said it will lend its considerable distribution and support
8/13/1999


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