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Software Functionality Revealed in Detail
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 engineering technical data

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 » engineering technical data

Developing a Universal Approach to Cleansing Customer and Product Data


Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

engineering technical data  Archiving Product Data | Engineering Data Product | Data Sheets Select Product | Product Data Management Category | Product Data Guide | Product Data Catalogue | Incorrect Product Data | Product Data Synchronization | Product Data Exchange | Product Data Quality | Technical Product Information | Product Data Sheet Search | Data Acquisition Toolbox | Product Data PDM | Product Data Management PDM | Find Product Data PDM | Looking for Product Data PDM | Managing Product Data PDM | Product Data Sheets PDM | Read More

Achieving a Successful Data Migration


The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

engineering technical data  capabilities, such as data re-engineering and cleansing, logical entity mapping, and logical attribute mapping. Informatica''s products support all these capabilities and best practices for migration, helping hundreds of leading organizations to migrate data and implement application projects while meeting timescales, budgets, and data quality requirements. For more information, please visit www.informatica.com/solutions/technology/migration to view the white paper, Accelerate Application Data Migration w Read More

Engineering Change Management 2.0: Better Business Decisions from Intelligent Change Management


Traditionally, change management in product development and engineering has been viewed as a way to control cost and improve efficiencies. But companies are becoming aware that better change can drive top-line benefits—and are developing processes with an eye towards improving speed-to-market. Find out why good change management is becoming more important—and how you can use it as a tool to increase product profitability.

engineering technical data  four key things in Engineering Change Management 2.0: Get the right supporting product data to the right people in a timely manner Formally analyze the impact of change on the product across the lifecycle and the supply chain, including technical and commercial considerations Collaborate visually about product change, with visualization and virtual meeting technology Develop and execute formal change implementation plans to put the decision into action These four key capabilities are the core requirements Read More

5 Keys to Automated Data Interchange


The number of mid-market manufacturers and other businesses using electronic data interchange (EDI) is expanding—and with it, the need to integrate EDI data with in-house enterprise resource planning (ERP) and accounting systems. Unfortunately, over 80 percent of data integration projects fail. Don’t let your company join that statistic. Learn about five key steps to buying and implementing EDI to ERP integration software.

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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.

engineering technical data  science degree in electrical engineering from the University of Rhode Island. He can be reached at davemc@neteos.com or 781-466-0100. Read More

A Roadmap to Data Migration Success


Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them.

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Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization


Malicious hacking and illegal access are just a few of the reasons companies lose precious corporate data every year. As the number of network security breaches increase, companies must find ways to protect data beyond the perimeter of their businesses. But how do they build a data-defensible architecture that will protect data on an ever-evolving network? The answer: by first developing an in-depth defense strategy.

engineering technical data  defined by the Internet Engineering Task Force (IETF) as the accepted standard for protecting data in transit over an untrusted network for Layer 3 protocols. IPSec is the mandated best practice for securing block-based storage protocols iSCSI, iFCP and FCIP. It is also quickly becoming the standard for protecting applications and data inside the enterprise network. IPSec provides three levels of data security: confidentiality, authentication and integrity. Confidentiality: Keeping the data secret. IPSec Read More

Data Management and Analysis


From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As).

For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

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Data Quality: A Survival Guide for Marketing


Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more.

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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

engineering technical data   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.

engineering technical data  customer data quality,data cleansing service,data integration system,data cleansing services,data profiling,data profiling software,data quality,data cleansing software,data governance,data integration Read More

Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

engineering technical data   Read More

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 "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

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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.

engineering technical data  Master Data Management,MDM,Customer Data Integration,CDI,Data Integration,CRM,BI,business intelligence,data standardization,data consolidation,Customer Relationship Management Read More