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Software Functionality Revealed in Detail
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 analysis of large data set from disparate sources


Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be

analysis of large data set from disparate sources  available. For a comprehensive analysis of some of the important principles and concepts in-memory technologies, I urge you to read an article titled In-Memory Analytics: A Multi-Dimensional Study written by my colleague Anna Mallikarjunan. Products with in-memory capabilities are not something new to the software industry. For example, the vendor QlikTech started working with their in-memory–based products in the 90s, and other BI application vendors such as IBM Cognos have been using them for more

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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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6 Ways You Can Benefit from Telecom Expense Management


A national health insurance company’s spreadsheet-based telecom management process was leading to time and money wasted as staff tried to make up for lack of spend visibility. Further pressure to prepare the telecom function for upcoming merger activity pushed the company to find a technology that would effect immediate cost savings and long-term telecom expense management. Read more about the solution the company chose.

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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 appearance of new and massive sources of information like the Web. Learn about tools you can use to turn Web data into an important asset for your organization.

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The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

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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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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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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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Soaring across the Regions: A View of the Impact of the Internet on Business


The Internet offers companies the opportunity to present a commercial image independent of size and location. With this and the Internet’s ability to extend a business’s reach, it is valuable to know precisely what various Internet service providers (ISPs) offer before buying. This includes evaluating service level and support capabilities and understanding how these vary throughout the United Kingdom (UK). Find out more.

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Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

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In-memory Computing: Lifting the Burden of Big Data


Business data is growing at an unprecedented speed, and organizations of all sizes, across all industries, have to face the challenge of scaling up their data infrastructure to meet this new pressure. Advances in server hardware and application design have led to a potential solution: in-memory computing. Read Aberdeen's Analyst Insight report and see how in-memory computing can address two of the "three Vs" of big data.

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