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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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 oracle customer data hub


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

oracle customer data hub  analytical and operational activities. Oracle 's Siebel Customer Data Integration is comprised of three solutions: Universal Application Network , Data Quality , and Universal 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

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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

Customer Care and Billing (CC&B)

Customer care and billing (CC&B) solutions typically support providers of utilities, telephony, cable, or other services providing companies. CC&B software includes functionality for mediation, provisioning, rating, reporting, financial systems, and billing for voice, data, content, and utility services. 

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Documents related to » oracle customer data hub

Developing a Universal Approach to Cleansing Customer and Product Data


Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

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Flexible Customer Data Integration Solution Adapts to Your Business Needs


Siperian's master data management and customer data integration (CDI) solutions allow organizations to consolidate, manage, and customize customer-related data. The type of CDI hub implemented depends on the CDI environment's maturity, requirements, and alignment with an organization's internal processes.

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Oracle Further Orchestrates Its SOA Forays Part Three: Strategy Shifts


Oracle has long moved in the direction of blurring the line between applications and infrastructure. It has leveraged the system of record elements in application suites by applying infrastructure technologies to correlate real-time events for improved decision-making.

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Where is Oracle in the Product Lifecycle Management Software Market?


Oracle is in the processing of developing their product lifecycle management capabilities. The question is whether they will accomplish this through the acquisition of a pure-play PLM vendor, or through internal technology development.

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Scalable Data Quality: A Seven-step Plan for Any Size Organization


Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.

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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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New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

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Data, Data Everywhere: A Special Report on Managing Information


The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and extract useful information, is harder still. Even so, this data deluge has great potential for good—as long as consumers, companies, and governments make the right choices about when to restrict the flow of data, and when to encourage it. Find out more.

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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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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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