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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 dictionary views


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

data dictionary views  it simply updates the data dictionary to reset a pointer from the partition to the table and vice versa. Because there is no physical movement of data, this exchange does not generate redo and undo, making it a sub-second operation and far less likely to impact performance than any traditional data-movement approaches such as INSERT. Lets assume we have a large table called Sales, which has daily range partitions. At the end of each business day, data from our online sales system needs to be loaded into

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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

Enterprise Incentive Management (EIM) RFI/RFP Template

Modeling and Strategic Analysis, Payee Database, Payee Sub-ledger, Compensation Plan Administration, Compensation Calculations, Views and Reports, Exception Data Resolution Management, Security and Compliance, Integration and Interfacing Requirements, Application Technology 

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ERP: Origins, Developments, and Trends


ERP first developed as a form of inventory control and later grew to link disparate bodies of information together from across the enterprise. Now, ERP enhancements include SCM, CRM, and e-commerce features, just to name a few. However, where is this technology going? What does it mean now?

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Glossary of Enterprise Applications Terminology Part Two: Just-in-Time to Extensible Markup Language


As enterprise applications systems developed over time, a continuous stream of new terminology surfaced. This is a glossary of those terms.

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Smaller Vendors Can Still Provide Relevant Business Systems Part Two: Market Impact


ERP and other enterprise applications products will thus demonstrate deep industry functionality and tight integration with best-of-breed 'bolt-on' products in a particular vertical, which also means adding sector-specific, fine-grained capabilities.

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Will Servigistics Click on More Service Cylinders? - Part 3


Part 1 of this blog series depicted the rise and fall of erstwhile public software company Click Commerce based in Chicago, Illinois (US). At the end of the post, I mentioned the merger of Servigistics and Click Commerce's Service Network Services (SNS) division. The private equity firm Marlin Equity Partners acquired both entities recently with the idea of forming a new combined company to solve

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


Read this white paper to learn about a lean form of on-demand data integration technology called data virtualization. Deploying data virtualization results in business intelligence (BI) systems with simpler and more agile architectures that can confront the new challenges much more easily.

All the key concepts of data virtualization are described, including logical tables, importing data sources, data security, caching, and query optimization. Examples are given of application areas of data virtualization for BI, such as virtual data marts, big data analytics, extended data warehouse, and offloading cold data.

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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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The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

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Data Management and Analysis


From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As).

For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

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The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

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