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Software Functionality Revealed in Detail
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 technical data base

Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

Compare Now

Core PLM--Product Data Management - Discrete RFI/RFP Template

Product Data Management (PDM), Engineering Change Order and Technology Transfer, Design Collaboration, Process and Project Management, Product Technology  

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Documents related to » technical data base

Data, Data Everywhere: A Special Report on Managing Information


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.

technical data base  to run into bureaucratic, technical and ethical problems. Online advertising is already far more accurately targeted than the offline sort, but there is scope for even greater personalisation. Advertisers would then be willing to pay more, which would in turn mean that consumers prepared to opt into such things could be offered a richer and broader range of free online services. And governments are belatedly coming around to the idea of putting more information—such as crime figures, maps, details of go Read More

A CRM System Needs A Data Strategy


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.

technical data base  embracing a variety of technical approaches - for gathering data from each contact with a customer or prospect. While each can support customer acquisition and retention efforts, data collection cannot be an end unto itself. In fact, a data strategy is needed to target and keep the right types of customers. For vendors and IT managers to help enterprise users, this is an overview of how they can develop and implement a data strategy to guide both the acquisition and retention phases of a marketing Read More

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 base  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 fu Read More

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.

technical data base  Source Data Products | Technical Product Data | True Data Products | Virtual Product Data | World Data Product | PMPO Product Data | PMPO Product Data Analyst | PMPO Product Data Base | PMPO Product Data Feed | PMPO Product Data File | PMPO Product Data Information | PMPO Product Data Mastering | PMPO Product Data Services | PMPO Product Data Solutions | PMPO Product Data Specialist | PMPO Product Data Standards | PMPO Advanced Data Products | PMPO Associated Data Products | PMPO Best Data Product | PMPO Read More

About Big Data


There may not be a consensus with respect to just how big "big data" is, but not many people will disagree that managing these huge amounts of data represents a challenge. TEC research analyst Jorge Garcia discusses the key issues surrounding big data, the different ways to manage it, and the major vendors offering big data solutions.

technical data base  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 traditional Read More

10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

technical data base  Errors to Avoid When Building a Data Center Proper data center commissioning can help ensure the success of your data center design and build project. But it''s also a process that can go wrong in a number of different ways. In the white paper Ten Errors to Avoid when Commissioning a Data Center , find out which mistakes to avoid when you''re going through the data center commissioning process. From bringing in the commissioning agent too late into the process, to not identifying clear roles for Read More

Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

technical data base  Mallikarjunan has held include technical lead and applications development manager of a team of .NET, data warehousing, and BI professionals for a fashion retail company. In this role, she was responsible for the development, maintenance, and support of Windows and Web-based applications, as well as an operational data store, data marts, and BI applications. Mallikarjunan holds a BSc in computer science from the University of Madras (India), and an MSc in computer science from Anna University in Madras, Read More

Deploying High-density Zones in a Low-density Data Center


New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center. The independence of these high-density zones allows for reliable high-density equipment operation without a negative impact on existing power and cooling infrastructure—and with more electrical efficiency than conventional designs. Learn more now.

technical data base  way, a variety of technical problems can be avoided. However, the spreading out strategy may not be viable for a number of reasons: Consumption of additional floor space, which may be difficult to justify or simply not possible Executive management perception that partially-filled racks are wasteful Increased cabling costs (because of longer runs) Increased cost and difficulty of maintenance '' cabling and mounting may be intertwined with other equipment in a nonstandard manner, scattered throughout the Read More

Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.

technical data base  for Owning versus Outsourcing Data Center Physical Infrastructure When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, Read More

Scalable Data Quality: A Seven-step Plan for Any Size Organization


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 base  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Read More

Informatica PowerCenter 5 Enables Enterprise Data Integration


Informatica Corporation’s Informatica PowerCenter 5 is a platform for integrating data to be deployed in e-Business applications, analytic applications and data warehouses, including a wide range of data sources, from enterprise resource planning (ERP) systems such as SAP R/3 and PeopleSoft, to web logs and Siebel applications. Market validation of its offerings is shown in a record Q4 of 2000, with a 150% increase in revenue over the previous year.

technical data base  PowerCenter 5 Enables Enterprise Data Integration Informatica PowerCenter 5 Enables Enterprise Data Integration M. Reed - April 5, 2001 Event Summary Informatica Corporation (NASDAQ: INFA), a provider of e-Business analytic software, has announced the availability of Informatica PowerCenter 5 , an enterprise data integration platform for the deployment and management of analytic applications and data warehouses. The vendor states that the Informatica PowerCenter 5 suite is designed to be a high Read More

Big Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone


Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and decision support.

technical data base  Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and Read More

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.

technical data base  rule to greater team Technical BA assigned Data Cleansed per business rule Integrity reports written, tested and moved to production Data Owners trained in daily maintenance of report The process takes about 6 weeks for each field to move from analysis to production support. This means at any given time 1 Senior Functional BA will have 12 to 18 fields opened at a time. Duration planning - If you have 50 fields to cleanse then you are looking at a 3 to 4 month effort, but if you have 200 fields to cleanse Read More

Customer Data Integration: A Primer


Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

technical data base  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization''s customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. Read More

Data Management and Business Performance: Part 1-Data


Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of

technical data base  Management and Business Performance: Part 1-Data Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a business intelligence (BI) solution. Two topics resounded: the use of BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of their data as well as to ways to capture the most valuable Read More