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Documents related to » technical data definition


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 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.

TECHNICAL DATA DEFINITION: A Definition of Data Warehousing A Definition of Data Warehousing M. Reed - August 18, 2002 Read Comments 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
8/18/2002

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.

TECHNICAL DATA DEFINITION: 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

IP Telephony: Project Definition Guide
You’ve determined the business rationale for embracing Internet protocol (IP) telephony as a strategy. Now it’s worth investing time in the project definition phase, since this will result in a clear statement of requirements that are in line with your objectives. However, how you define the project will depend on the needs of your business and your plans for convergence.

TECHNICAL DATA DEFINITION:
1/22/2007 2:39:00 PM

Employee Onboarding: An HR Technology Seeking a Definition
A commonsense approach to defining an onboarding initiative starts with the company defining its objectives, prioritizing its goals, and carefully evaluating the options. When considering human resources technology specifically designed with the onboarding process in mind, you should focus on the flexibility of the onboarding solution options. Learn more about managing employee onboarding with an automated solution.

TECHNICAL DATA DEFINITION:
6/29/2009 12:11:00 PM

Curing the Data Integration Migraine
The potential value of centralized data integration is enormous. Once implemented, integration systems promise to deliver more accurate and higher quality data. However, for those who venture into the world of implementation, the promise rarely matches the reality. Avoiding the “data integration migraine” requires careful planning to reduce the risks associated with data relationship, transformation, and map discovery.

TECHNICAL DATA DEFINITION: Curing the Data Integration Migraine Curing the Data Integration Migraine Source: Exeros Document Type: White Paper Description: The potential value of centralized data integration is enormous. Once implemented, integration systems promise to deliver more accurate and higher quality data. However, for those who venture into the world of implementation, the promise rarely matches the reality. Avoiding the “data integration migraine” requires careful planning to reduce the risks associated with data
10/27/2006 4:30:00 PM

A Guide to Intelligent Data Auditing
Data auditing is a form of data protection involving detailed monitoring of how stored enterprise data is accessed, and by whom. Data auditing can help companies capture activities that impact critical data assets, build a non-repudiable audit trail, and establish data forensics over time. Learn what you should look for in a data auditing solution—and use our checklist of product requirements to make the right decision.

TECHNICAL DATA DEFINITION: A Guide to Intelligent Data Auditing A Guide to Intelligent Data Auditing Source: Tizor Document Type: Checklist/Guide Description: Data auditing is a form of data protection involving detailed monitoring of how stored enterprise data is accessed, and by whom. Data auditing can help companies capture activities that impact critical data assets, build a non-repudiable audit trail, and establish data forensics over time. Learn what you should look for in a data auditing solution—and use our checklist of
3/19/2008 6:06:00 PM

Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

TECHNICAL DATA DEFINITION: Overall Approach to Data Quality ROI Overall Approach to Data Quality ROI Source: SAP Document Type: White Paper Description: Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an
3/16/2011 5:34:00 PM

Implementing Energy-Efficient Data Centers
But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...

TECHNICAL DATA DEFINITION: Implementing Energy-Efficient Data Centers Implementing Energy-Efficient Data Centers Did you realize that your data center(s) may be costing you money by wasting electricity ? Or that there are at least 10 different strategies you can employ to dramatically cut data center energy consumption ? The fact is, most data centers are not designed with energy efficiency in mind. But in the white paper Implementing Energy-efficient Data Centers , you ll learn how to save money by using less electricity—whether
6/18/2009

Siemens’ JT Data Format Gets a Nod from ISO » The TEC Blog
Siemens’ JT Data Format Gets a Nod from ISO » 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

TECHNICAL DATA DEFINITION: 3d visualization, CAD, JT ISO standard, plm, Siemens JT, Siemens JT data format, Siemens PLM Software, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
29-01-2013

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 ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no wonder the complaint resolution pipeline is backed up. Think it’s your customer resource management (CRM) system? Think again. It’s bad data, and it’s costing you millions. Request your copy of The Bottom Line on Bad Customer Data that delivers detailed advice from Jill Dyche, partner and co-founder of Baseline Consulting, about what you can do to 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.

TECHNICAL DATA DEFINITION:   Scientific,   and Technical Consulting Services,   Management of Companies and Enterprises Related Keywords:   problem,   structure,   baseline,   Customer,   bad,   data Source: Baseline Consulting Learn more about Baseline Consulting Readers who downloaded this white paper also read these popular documents! Best Practices for ERP Implementation TEC 2013 Supply Chain Management Buyer’s Guide Extending BI’s Reach: Anticipate Outcomes, Forecast Results, and Respond Proactively How Mobile
5/25/2005 10:37:00 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.

TECHNICAL DATA DEFINITION: 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


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