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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 entry outsourcing projects


Outsourcing 101 - A Primer
Outsourcing is a very diverse topic, and there are many different outsourcing options and outsourcing service providers to choose from. Companies are telling

data entry outsourcing projects  pension and 401k benefits, data transcription, and call center operations. This realm is made more and more possible by continued investment in education, improved information technology, the wide adoption of the Internet, and the broad, but still emerging, availability of low cost telecommunications and data communications in third world countries. How Does It Work? How does a company engage and pay for the services of an outsourcing provider? Simply, the company contracts with an outsourcing provider

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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 » data entry outsourcing projects

The Many Flavors of Application Software Outsourcing


Many companies are looking to outsource development and maintenance of their application software. Common reasons that companies outsource application software are to reduce their costs, improve quality, obtain flexible staffing levels, and obtain improved service and support so they can focus on their core competence such as, designing clothes, managing equity portfolios, or running hospitals. Choosing whether to outsource or not is a strategic decision for a company. Once a company has decided to outsource, however, it must still choose an outsourcing approach that best fits it needs. This paper will describe the many different options for application software outsourcing, including the advantages and disadvantages of each alternative.

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Improving Business Integration for a Competitive Advantage in the Mid-market


Mid-market companies can level the competitive playing field by using business integration technology. Integrated processes reduce costs by decreasing data entry errors, improving supply chain responsiveness, and increasing inventory accuracy—not to mention eliminating document processing fees and customer charge-backs. But how can mid-market companies leverage the capabilities of "high-end" integration solutions?

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Five HR Technologies You Should Know


Almost everything you know about human resources (HR) outsourcing is about to change. The future is about single-source integration, and there are key new technologies that herald this era: unified service for HR, time, payroll, and expense tracking; management dashboards; streamlined employee interfaces; synchronous data with a single database; and empowered reporting.

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Nearshoring: Looking Closer to Home


Companies looking for savings but worried about the risks and cultural barriers involved in offshore outsourcing, whose business processes have a strong customer focus or regulations-driven reporting element, could benefit from nearshoring. Nearshoring involves outsourcing work to companies with the economic benefits of an offshore location, but a closer cultural, linguistic, and geographic fit with the user organisation.

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The Teradata Database and the Intelligent Expansion of the Data Warehouse


In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Data Warehouse in detail, including functionality, distinguishing characteristics, and Teradata's role in the competitive data warehouse space.

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Data Center Projects: Advantages of Using a Reference Design


It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are defined and their benefits are explained.

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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.

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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.

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Agile Data Masking: Toward a More Secure and Agile Enterprise


Data masking has long been a key component of enterprise data security strategies. However, legacy masking tools could not deliver secure data, undermining their impact. This white paper explores how data as a service can deliver on the promise of masking, while increasing organizational flexibility and agility.

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Business Basics: Unscrubbed Data Is Poisonous Data


Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data quality is low, and the short- and long-term benefits are great.

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