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Documents related to » technical data sheets plm


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 SHEETS PLM: 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

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.

TECHNICAL DATA SHEETS PLM: 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

iWeb Agilewiz BPMS - iWeb Technical Framework
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TECHNICAL DATA SHEETS PLM: Agilewiz BPMS - iWeb Technical Framework iWeb Agilewiz BPMS - iWeb Technical Framework Source: iWeb Technology Solutions Document Type: Brochure Description: ... iWeb Agilewiz BPMS - iWeb Technical Framework style= border-width:0px; />   comments powered by Disqus Source: iWeb Technology Solutions Learn more about iWeb Technology Solutions
7/10/2013 5:00:00 PM

Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g for Data Warehousing and Business Intelligence. Find RFP Templates and Other Solutions to Define Your Project In Relation To Oracle Database, Data Warehousing and Business Intelligence. Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

TECHNICAL DATA SHEETS PLM: Oracle Data Mining helps technical professionals find patterns in their data, identify key attributes, discover new clusters and associations, and uncover valuable insights. To address these business problems, Oracle Data Mining allows companies find new information from their data using a wide range of state-of-the-art algorithms. Data mining algorithms are machine-learning techniques for analyzing data to discover patterns and relationships. Oracle provides multiple algorithms since different
4/20/2009 3:11:00 PM

Massive Data Requires Massive Measures
There’s a lot of “big” money to be made these days when it comes to the analysis of big data. Find out what the key components are in this special report. One thing we learned in the data warehouse and data management world is that when it comes to the analysis of big data, there is also a lot of big money involved in order to gain position. But is the analysis of extensive amounts of data really a key component for the corporate business world?

TECHNICAL DATA SHEETS PLM: database involves not only technical criteria but also business-related criteria. Besides this spending rush, many other things are happening in the data warehouse space that are worth mentioning, such as the adoption of non-conventional database solutions such as Nosql , and distributed databases as well as the adoption of special types of technologies such as in-memory analysis technologies or column-oriented databases . There are also topics we will have to cover in future articles related to the big
11/5/2010 10:03:00 AM

Data Center Automation
With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands.

TECHNICAL DATA SHEETS PLM: Data Center Automation Data Center Automation Source: Quocirca Ltd Document Type: White Paper Description: With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response
10/30/2007 6:19:00 PM

Data Quality Trends and Adoption
While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

TECHNICAL DATA SHEETS PLM: Data Quality Trends and Adoption Data Quality Trends and Adoption Source: SAP Document Type: White Paper Description: While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies
3/22/2011 9:46:00 AM

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 SHEETS PLM: 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

About Big Data
TEC analyst Jorge Garcia discusses the key issues surrounding big data, the different ways to manage it, and the major vendors offering big data solutions. There may not be a consensus with respect to just how big

TECHNICAL DATA SHEETS PLM: data solution provides the technical means to perform operations with high volumes of data in a short period of time, with the ability to treat various types of data from disparate sources. Why the Hype? One of the main triggers for the design of new applications and technologies is the inability of common BI deployments to manage both structured and unstructured content. The data extraction process can be especially difficult with large amounts of information. These new tools are changing the
11/18/2011 2:08:00 PM

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.

TECHNICAL DATA SHEETS PLM: Maintenance , Springfield: National Technical Information Service, US Department of Commerce) Critical failures are, by their very nature, serious. When they occur they are often designed out, or a replacement asset is installed, or some other initiative is put in place to ensure that they don t recur. As a result, the volume of data available for analysis is often small, and therefore the ability of statistical analysis to deliver results within a high level of confidence is questionable at best. This
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.

TECHNICAL DATA SHEETS PLM: on the website. The technical integration with SAP IS-U did succeed. But it didn t work out well... When a customer started using the website, he would typically see only part of his data. The reason: lots of customers had multiple customer records, each telling part of the truth about the customer. The explanation: one customer record might come from the company selling natural gas in his region; a second customer record might come from yet another company selling electricity; the third from a former
8/23/2002


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