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Software Functionality Revealed in Detail
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 umts data call flow


Microsoft Goes Their Own Way with Data Warehousing Alliance 2000
Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 vendors throughout the industry have qualified for Microsoft« Data

umts data call flow  Goes Their Own Way with Data Warehousing Alliance 2000 Event Summary REDMOND, Wash., Nov. 30 /PRNewswire/ -- Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 top vendors throughout the industry have qualified for Microsoft Data Warehousing Alliance 2000. Alliance members and partners are committed to delivering tools and applications based on the Microsoft Data Warehousing Framework 2000, an open architecture for building business intelligence and analytical a

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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

CRM for Financial and Insurance Markets RFI/RFP Template

Insurance and Investment, Marketing Automation, Sales Force Automation (SFA), CRM Analytics, Call Center and Customer Service, Professional Services Automation (PSA), e-CRM, E-Mail Response Management, Industry Vertical Module Availability, Product Technology  

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Informatica PowerCenter 5 Enables Enterprise Data Integration


Informatica Corporation’s Informatica PowerCenter 5 is a platform for integrating data to be deployed in e-Business applications, analytic applications and data warehouses, including a wide range of data sources, from enterprise resource planning (ERP) systems such as SAP R/3 and PeopleSoft, to web logs and Siebel applications. Market validation of its offerings is shown in a record Q4 of 2000, with a 150% increase in revenue over the previous year.

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Understanding the PCI Data Security Standard


The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a proactive rather than passive way. These include security management, policies, procedures, network architectures, software design, and other protective measures. Get a better understanding of the PCC DSS and learn the costs and benefits of compliance.

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Achieving a Successful Data Migration


The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

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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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Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever


Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.

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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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Agile Data Masking: Critical to Data Loss Prevention and Threat Reduction


Over the past several years data loss and data leaks have been a regular part of headline news. This surge in data leak activity has prompted many organizations to reevaluate their exposure to data leaks and institute automated, agile approaches to data masking. Well-implemented data masking secures data delivery and enhances compliance and security while accelerating data management processes.

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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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Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

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Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

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