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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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 disadvantages data profoling


Should Your Software Selection Process Have a Proof of Concept? Part Two: Advantages, Disadvantages, and Conclusion
A proof of concept (POC) should be completed as part of the selection process when the risk of project failure is comparatively high. Risk can be measured by

disadvantages data profoling  and Conclusion Advantages and Disadvantages to the Client There are a number of advantages to the proof of concept (POC) for the client including Expectation synchronization with the vendor Improved ownership of the implementation process Identification of functional gaps or overselling Better understanding of investment required. More accurate scoping provides a better understanding of the investment required to complete the implementation. Evaluation of the implementation partner. The POC process

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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

Outsourcing, IT Infrastructure

The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical types of activities that these providers perform include data center operations; network operations; backup/recovery services, data storage management services; system administration services; end user support of desktop PCs, laptops, and handheld devices; web site, or application hosting, etc.  

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Documents related to » disadvantages data profoling

UNIT4 and Multitenancy


Among the interesting developments at the recent Grape Escape event in Boston was the announcement of UNIT4’s multitenant model for its Agresso ERP offering, which generated a great deal of discussion, if not some controversy. So, UNIT4 boasts five key deployment capabilities for Agresso ERP: A virtual machine (VM) environment option A private cloud environment option An

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The Advantages of Row- and Rack-oriented Cooling Architectures for Data Centers


The traditional room-oriented approach to data center cooling has limitations in next-generation data centers. Next-generation data centers must adapt to changing requirements, support high and variable power density, and reduce power consumption and other operating costs. Find out how row- and rack-oriented cooling architectures reduce total cost of ownership (TCO), and address the needs of next-generations data centers.

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Containerized Power and Cooling Modules for Data Centers


Standardized, pre-assembled, and integrated data center facility power and cooling modules are at least 60% faster to deploy, and provide a first cost savings of 13% or more compared with traditional data center power and cooling infrastructure. Facility modules, also referred to in the data center industry as containerized power and cooling plants, allow data center designers to shift their thinking from a customized “construction” mentality to a standardized “site integration” mentality. This white paper compares the cost of both scenarios, presents the advantages and disadvantages of each, and identifies which environments can best leverage the facility module approach.

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Are You Tuned into Radio Frequency Identification?


This article examines the organizational fit of radio frequency identification (RFID) and its technology’s basic mechanics. Its prohibitive costs often account for the decision to not implement RFID. Yet some factors influencing adoption may shed new light on why RFID is important.

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The Value of Big Data


As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value.

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A Solution to Data Capture and Data Processing Challenges


Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems.

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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...

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Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

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Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

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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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