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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.
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 data request rejection letter template


A Road Map to Data Migration Success
Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project

data request rejection letter template  Road Map to Data Migration Success Our consultants can help you optimize your end-to-end data migration by combining our expertise with our SAP BusinessObjects software to integrate your data and improve the data’s quality, particularly when upgrading or replacing legacy systems with SAP ERP. Source: SAP Resources Related to A Road Map to Data Migration Success : Data Migration (Wikipedia) A Road Map to Data Migration Success Data Migration Project is also known as : Road Map Data Migration Success

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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 » data request rejection letter template

Data Quality Strategy: A Step-by-Step Approach


To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

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Meet PCI DSS Compliance Requirements for Test Data with Data Masking


Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more.

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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.

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The Importance of a Single Product for Data Quality and Data Integration


Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data.

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TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center


Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the two architectures, and illustrates the key drivers of both the capex and opex savings of the improved architecture.

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Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

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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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Types of Prefabricated Modular Data Centers


Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

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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.

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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.

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