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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...
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Documents related to » implementing data warehouse etl


Best Practices for a Data Warehouse on Oracle Database 11g
Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW

implementing data warehouse etl  Data Warehouse Info | Implementing Data Warehouse | Data Warehouse Process | Implementing Real Time Data Warehousing | Data Warehouse System Complete | Data Warehouse EDW | Data Warehouse Architecture EDW | Data Warehouse Concepts EDW | Data Warehousing Information Center EDW | Data Integration Paper EDW | Data Warehouse Software EDW | Data Warehousing Analysis EDW | Data Warehouse Community EDW | Data Warehouse Automation EDW | Perspectives on Data Warehousing EDW | Data Warehousing OLAP EDW | Resource Read More...
The Evolution of a Real-time Data Warehouse
Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine

implementing data warehouse etl  the technical difficulties of implementing a true real-time data warehouse, there are some advantages. It shortens information delivery times. It improves integration throughout the organization. It eases the analysis of future trends. Basic Principles to Consider With the growing popularity and increasing implementation of real-time data warehouses, it is important to consider some basic principles when considering a real-time data warehouse implementation. Data on Time, at the Right Time . The data Read More...
Optimizing Gross Margin over Continously Cleansed Data
Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards

implementing data warehouse etl  content, or those simply implementing a database, have exposed the magnitude of the problem. While these initiatives are great starts, solving your internal requirement for truly cleansed data, ready for your company’s use, is not a single leak with a quick fix. Rather, a holistic approach is required to address all aspects -including aggregating data from all potential sources (backend ERP systems, suppliers, marketing systems, 3rd party content providers and vendors) and establishing business rules Read More...
A Road Map to Data Migration Success
Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project

implementing data warehouse etl  processes that they are implementing. Allow time in your planning for changes to the mapping, business rules, and re-loads. It is not uncommon for there to be confusion during beta testing and implementation as to where errors originate. It''s all too easy for bad data to be blamed for every test error. What can you do as part of your planning to avoid this? Implement the migration with as much metadata and reconciliation as possible. Not only are you ensuring the integrity of your data, you are Read More...
More Data is Going to the Cleaners
WESTBORO, Mass., November 29, 1999 - Ardent Software, Inc. (Nasdaq: ARDT) today announced a strategic partnership with Firstlogic, Inc., the developer of i.d

implementing data warehouse etl  Ardent''s DataStage Suite. Organizations implementing complex database marketing programs and e-business strategies depend on extensive data quality assurance. Together Ardent and Firstlogic are meeting this market need, said Mikael Wipperfeld, vice president of data warehouse marketing at Ardent Software. This partnership allows our joint customers to take advantage of Firstogic''s address verification, name parsing and extensive matching and consolidation capabilities inside the DataStage suite, the Read More...
Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise
While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to

implementing data warehouse etl  Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help. BEG Read More...
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

implementing data warehouse etl  the PCI Data Security Standard MessageLabs Hosted Web Security and Content Filtering service operates at the Internet level, intercepting viruses, and spyware. Source : MessageLabs | Now part of Symantec Resources Related to Understanding the PCI Data Security Standard : Payment Card Industry Data Security Standard (PCI DSS) (Wikipedia) Understanding the PCI Data Security Standard Data Security is also known as : Data Security Architecture , Data Security Articles , Data Security Audit , Read More...
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

implementing data warehouse etl  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More...
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

implementing data warehouse etl  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. Read More...
Fundamentals of Managing the Data Center Life Cycle for Owners
Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and

implementing data warehouse etl  of Managing the Data Center Life Cycle for Owners Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and Read More...
Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses
Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has

implementing data warehouse etl  Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and pre Read More...
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

implementing data warehouse etl  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. 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

implementing data warehouse etl  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...
Linked Enterprise Data: Data at the heart of the company
The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet

implementing data warehouse etl  Enterprise Data: Data at the heart of the company The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, Read More...
Master Data Management and Accurate Data Matching
Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are

implementing data warehouse etl  Data Management and Accurate Data Matching Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process. Read More...

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