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 engineering technical data

Browse RFP templates

Visit the TEC store for RFP templates that can save you weeks and months of requirements gathering, and help ensure the succes of your software selection project.

Browse Now
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

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.

engineering technical data  from MIT in electrical engineering where he did his thesis on the analysis of a 200MW power supply for a tokamak fusion reactor. From 1979 to 1981, he worked at MIT Lincoln Laboratories on flywheel energy storage systems and solar electric power systems. Victor Avelar is a Strategic Research Analyst at APC. He is responsible research in data center design and operations and consults with clients on risk assessment and design practices to optimize the availability of their data center environments. Victor 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

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

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

Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

engineering technical data  data blending, data analyst, data source, data analysis, data software, data cleansing, data access, data blending software 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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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.

engineering technical data  Path to Healthy Data Governance through Data Security 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 organization. This article is devoted to providing insight and outlining the steps that will put you on the path Read More

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

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.

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Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever


Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.

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Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

engineering technical data  data visualization, IBM Cognos Business Intelligence, business intelligence, data delivery, data visualization best practices Read More

Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

engineering technical data  data warehouse, data integration tools, data integration toolbox, big data management, data exploration tools, master data management, data management platform Read More