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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 quality


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.

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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

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 water treatment plant. ERP software for Municipalities nearly always includes Finance, Customer Care and Billing For a complete municipal ERP suite, the following modules are usually included: - Human Resources - Maintenance Management - Asset Management - Project Management ( including Grant Management) - Quality Management - Analytics - Product Technology Of the above, Project and Quality Management modules may not be required for smaller Municipalities.    

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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, usability, and availability of their customer relationship management (CRM) solutions. How do you know if your CRM system performs for each user? What does it mean when users say the system is slow? An experience management solution can give you the answers.

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

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.

siebel data quality  CRM, and synchronize between Siebel and accounting application. Benefit: Solve more than 97 percent of data quality issues, reuse more than 40 percent of integration processes to accelerate development, retire legacy systems. Craft Your Strategy, Choose The Right Tools And Beat The Odds Data migration problems often derail valuable application projects and provoke ‘blame storms' that affect even the most skilled and conscientious business and IT staff. But it doesn't have to be this way. Organizations 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 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.

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

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.

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 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.

siebel data quality  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. Read More

Big Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone


Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and decision support.

siebel data quality  Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and Read More

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.

siebel data quality  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. Read More

Operationalizing the Buzz: Big Data 2013


The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use to explore why and how companies are utilizing Big Data. Download the report and get all the results.

siebel data quality  the Buzz: Big Data 2013 The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and Read More

Types of Prefabricated Modular Data Centers


Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

siebel data quality  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More

Data Storage in the Cloud-Can you Afford Not To?


Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

siebel data quality  Storage in the Cloud-Can you Afford Not To? Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage. Read More

Data Center Automation


With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands.

siebel data quality  Center Automation With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands. Read More

The Data Explosion


RFID and wireless usage will drive up data transactions by ten fold over the next few years. It is likely that a significant readdressing of the infrastructure will be required--in the enterprise and the global bandwidth.

siebel data quality  Data Explosion Introduction Traffic on the World Wide Web continues to grow. Traffic on your S mall S mart F ast devices continues to grow. Ok, I admit it. I bought the cell phone that takes pictures. I didn't know if it was useful; but being a technophile, I went for it. And rapidly it all came to me! I tried on a new cool jacket ... I crooned over it ... but for that much money, I wasn't sure. Should I really buy this? Enter the pic in my cell phone! We chicks have our honor guard. You know those Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

siebel data quality  Necessity of Data Warehousing The Necessity of Data Warehousing M. Reed - August 2, 2000 Why the market is necessary Data warehousing is an integral part of the information age . Corporations have long known that some of the keys to their future success could be gleaned from their existing data, both current and historical. Until approximately 1990, many factors made it difficult, if not impossible, to extract this data and turn it into useful information. Some examples: Data storage peripherals such Read More

The Fast Path to Big Data


Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

siebel data quality  Fast Path to Big Data Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise Read More