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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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 web data extraction


Collecting Meaningful Data from the Web: Once an Impossibility, Now a Reality
The traditional way of extracting data from disparate data sources has been transformed by the emergence of new tools and applications, as well as the

web data extraction  specific needs by offering Web data integration tools to collect data—bypassing the use of an API, and concentrating on collecting this information by taking advantage of Web-based protocols like extensible markup language ( XML ), hypertext markup language ( HTML ), JavaScript , or simple object access protocol ( SOAP ) (among other technologies) to extract this information. This task is by no means easy, since standardization of various Web technologies is required for extracting data and

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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 » web data extraction

Access to Critical Business Intelligence: Challenging Data Warehouses?


There is a perception that if business users are given access to enterprise databases and raw query tools, they will create havoc in the system, which is a possibility—unless the business intelligence (BI) product developer understands the potential problem and addresses it as a business-critical factor.

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Best Practices for a Data Warehouse on Oracle Database 11g


Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

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The Web-based Sales Portal-A Catalyst for Business Transformation


A sales portal is one of many tools that can be used to help transform a business, especially a consumer packaged goods company. In this article, key structural and functional elements, as well as the advantages of implementing and effectively using a sales portal, are discussed.

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Enterprise Application Integration - the Latest Trend in Getting Value from Data


Enterprise Application Integration (EAI) is one of the hot-button issues in IT for the Year 2000. Information Week Research's survey of 300 technology managers showed nearly 75% of respondents said EAI is a planned project for their IT departments in the coming year. According to a survey conducted by Bank Boston, the market for EAI is expected to be $50 Billion USD by 2001. However, successful EAI requires a careful combination of a middleware framework, distributed object technologies, and custom consulting.

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Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond


For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.

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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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The Path to Healthy Data Governance


Many companies are finally treating their data with all the necessary data quality processes, but they also need to align their data with a more complex corporate view. A framework of policies concerning its management and usage will help exploit the data’s usefulness. TEC research analyst Jorge Garcia explains why for a data governance initiative to be successful, it must be understood as a key business driver, not merely a technological enhancement.

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2012 Business Data Loss Survey results


This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now.

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ESG - Riverbed Whitewater: Optimizing Data Protection to the Cloud


Riverbed Whitewater leverages WAN optimization technology to provide a complete data protection service to the cloud. The appliance-based solution is designed to integrate seamlessly with existing backup technologies and cloud storage provider APIs. Read this ESG Lab report on hands-on testing of the Riverbed Whitewater appliance for ease of use, cost-effective recoverability, data assurance, and performance and scalability.

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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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