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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 quality  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. Read More...
ERP for Municipalities
In this model, we assume the municipality controls water, sewers and roads. We assume also that it collects municipal or county taxes and manages many of its own assets such as vehicles and wate...
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Documents related to » siebel data quality


Best Practices in Siebel CRM Performance Management: Monitor, Measure, and Manage the End-user Experience
Many frustrated executives find that despite the fortune spent on managing servers, networks, and applications, there are still complaints about the performance

siebel data quality  solution automatically 'sees' every Siebel transaction and the steps that the user is taking before, during and after the transaction. Knoa EPM's self-discovery capabilities eliminate, completely, the need for customers to design a data collection strategy, define transactions to the system or train the system to recognize new transactions. Automated Discovery means: No up-front requirements definition or project scoping Faster implementation using out-of-the-box templates lower overall cost of ownership Read More...
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

siebel data quality  as Informatica PowerConnect for Siebel and Informatica PowerConnect for IBM MQSeries (which includes real-time data integration capabilities), as well as enhanced versions of Informatica PowerConnect for SAP R/3 and Informatica PowerConnect for PeopleSoft . The new architecture also provides native support for leading e-Business data types, such as XML and clickstream, as well as substantial increases in performance and scalability . Together, these connectivity options should allow companies to Read More...
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.

siebel data quality  , Oracle , and Siebel . Because many organizations build their information structures based on these three platforms, the natural integration of Siperian's offerings with these products ensures seamless integration. Siperian delivers out-of-the-box, industry-specific models within the following industries: health and life sciences, financial services, high-tech, manufacturing, and communications and media. Companies in these industries can take advantage of these models, as these models meet many of Read More...
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

siebel data quality  as Oracle, PeopleSoft, and Siebel. Data quality -a component for the profiling, cleansing, enhancement, matching, consolidation, and monitoring of data (BusinessObjects Data Insight XI and BusinessObjects Data Quality XI). This component is described in more detail below. Metadata management -a component that collects and unifies metadata from BI objects, ETL products, relational databases, modeling tools, and thirdparty solutions. IT staff and business analysts use a thin-client Web interface to explore Read More...
Data Migration Best Practices
Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce

siebel data quality  Migration Best Practices Large-scale data migrations can be challenging, but with the appropriate planning—and through careful execution of that plan—organizations can greatly reduce the risks and costs associated with these projects. This paper offers a handy checklist of issues to consider before, during, and after migration. Read More...
Data Quality Trends and Adoption
While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ

siebel data quality  Quality Trends and Adoption While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers. Read More...
How Companies Use Data for Competitive Advantage
Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage.

siebel data quality  Companies Use Data for Competitive Advantage How Companies Use Data for Competitive Advantage Today, many businesses find they are under siege dealing with an explosion of data. Yet the best performing companies are mastering their data—and using it for competitive advantage. How are they able to accomplish this? What best practices, approaches, and technologies are they employing? Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage . In this Economist Business Read More...
Logs: Data Warehouse Style
Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources

siebel data quality  Data Warehouse Style Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency. Read More...
Guide to Quality Assurance
In today’s world, current and future customers are interested to know whether or not you have implemented a quality control system. Some customers will demand

siebel data quality   Read More...
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

siebel data quality  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. Read More...
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

siebel data quality  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. Read More...
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

siebel data quality  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. Read More...
Data Storage in the Cloud--Can You Afford Not To?
In Data Storage in the Cloud Can You Afford Not To?

siebel data quality  Storage in the Cloud--Can You Afford Not To? Spiraling data storage requirements are straining many companies' abilities to keep pace. One obvious solution is storage in the cloud—but concerns regarding security, speed, and accessibility remain. Or do they? In Data Storage in the Cloud—Can You Afford Not To? , you'll discover a cloud storage solution that offers you high-security dual-level encryption (SSLv3 and 256-bit AES) data accessibility from anywhere lower costs due to the economies of Read More...
Analyzing Big Data: The Path to Competitive Advantage
Big data is different from ordinary database information because of the massive volume, the variety, and the velocity. And the data mix now includes product

siebel data quality  Big Data: The Path to Competitive Advantage Big data is different from ordinary database information because of the massive volume, the variety, and the velocity. And the data mix now includes product reviews, video, blogs, tweets, and more. But the biggest current challenge may be to articulate a compelling business case for using big data. Find out how companies in various industries are finding value in the data they have already collected and making it actionable. Read More...
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