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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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 siebel data warehouse


Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a

siebel data warehouse  Customer Master . Oracle's Siebel Data Quality identifies duplicate customer records and provides pre-built integration to third-party data cleansing tools. Oracle's matching server functionality allows the organization to search, match, and identify duplicate customer records based on key customer attributes such as name and address. The data quality connector provides real-time and batch request capabilities that connect to an external data cleansing engine to eliminate duplicate customer records. Addit

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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

Warehouse Management Systems (WMS)

A warehouse management system (WMS) should provide database and user-level tools in order for a company to optimize its storage facilities while at the same time providing user level task direction and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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Documents related to » siebel data warehouse

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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EAI Vendor MITEM Integrates Legacy Systems With Siebel


MITEM Corporation has announced that its legacy application integration software MitemView 5.3 has been validated by Siebel Systems for its Siebel eBusiness Applications. As more EAI vendors vie for market share, having their connectors/adapters certified by the vendor of the target application may become a key to product sales and competitive advantage.

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Informatica Powers Siebel’s New eBusiness Analytics


Siebel Systems is incorporating Informatica’s data integration platform into Siebel eBusiness Analytics 2000.3. The vendors hope to use the integrated product to consolidate data into a 'comprehensive e-business data warehouse'. Have the vendors found the e-business holy grail?

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Attaining Real Time, On-demand Information Data: Contemporary Business Intelligence Tools


Demand for instant access to dispersed information is being met by vendors offering enterprise business intelligence tools and suites. Portlet standardization, enterprise information integration, and corporate performance management are among the proposed solutions, but do they really deliver real time information?

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Big Data: Operationalizing the Buzz


Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more.

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TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center


Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the two architectures, and illustrates the key drivers of both the capex and opex savings of the improved architecture.

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Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations


While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of "big data" and the use of analytics to mine that data.

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Protecting Critical Data


The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly.

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Data Masking: Strengthening Data Privacy and Security


Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.

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Six Steps to Manage Data Quality with SQL Server Integration Services


Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

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