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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

data warehouse type  Practices for a Data Warehouse on Oracle Database 11g Best Practices for a Data Warehouse on Oracle Database 11g If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Oracle has been helping customers like you manage your business systems and information with reliable, secure, and integrated technologies. Source : Oracle Resources Related to Data Warehouse : Data Warehouse (Wikipedia) Best Practices for a Data Warehouse on Oracle Read More...
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 » data warehouse type


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

data warehouse type  The development of a data warehouse and the consolidation of information across the organization is an example of how data integration is applied in organizations. Sub-sets of data from disparate locations within the organization are loaded into the centralized structure of a data warehouse or dedicated database. This centralized structure creates a specified view of data to measure an organization's performance, to generate reports, to provide analytics, and so forth. Not all data integration is equal Read More...
About Big Data
There may not be a consensus with respect to just how big

data warehouse type  data hype. A corporate data warehouse can rapidly become expensive as the data volume increases. Scaling a data warehouse can be a burden when you’re dealing with such volumes. Meanwhile, some big data providers can produce solutions not only that are cheaper from the get go, but which can be escalated, adapted, and modified as required. Open source solutions—such as NoSQL—have also played an important role in the big data movement, forcing market prices to stay down. The Players As with any other Read More...
Warehouse Management for Manufacturers: Why Extended ERP Might Be the Right Choice
As a provider of enterprise resource planning (ERP) integrated workforce productivity solutions, we have seen many approaches to distribution automation. Adding

data warehouse type  productivity suite, which includes data collection, mobile devices, truck mounted devices, and the ability to direct workers to the next task. This approach delivers functionality for picking and warehouse automation, driving efficiencies to and automating the work of people performing those functions. A WMS might accomplish some of the same things, but it brings the added cost of additional licenses for the application and database, additional server hardware, additional support and maintenance fees, Read More...
Warehouse Management Systems by the Numbers
When it comes to warehouse management systems (WMS), the stats are both shocking and thought-provoking. And although you don't see these stats in the marketing

data warehouse type  will continue to gather data and take it back to your manager, vice president, president, and so on, only to have them again shoot down the idea of investing in a WMS system. Tell them a WMS system will also lower the total cost per unit shipped; reduce the number of inventory out-of-stocks; improve delivery accuracy and timeliness; increase profitability per order and per customer; reduce customer service cost; reduce phone communication costs; and increase sales. Now is the time to take a serious look Read More...
Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond
For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet

data warehouse type  A Methodology to Sustaining Data Integrity for Going Live and Beyond For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data. Read More...
Is Your Warehouse Ready for the Upswing?
Supply chain management is a long-term strategy. The centerpiece for supply chain execution—the warehouse management system (WMS)—is an excellent place to start

data warehouse type  Operating Efficiency | Real-time Data | SOA | Support Changing Customer Requirements | Maximizing Staff Productivity | Increase Customer Satisfaction | Maximizing Products | Maximizing Available Storage Space | Help Business Reduce Labor Costs | Maximizing Equipment | High Jump Warehouse Management System Vendors | Slotting Products | Maximize Space Utilization | Reducing the Distance Pickers Travel | Adapt to Changing Business Conditions | Visibility of Trailers and Their Locations | Increase Read More...
Implementing Energy-Efficient Data Centers
But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...

data warehouse type  Energy-Efficient Data Centers Did you realize that your data center(s) may be costing you money by wasting electricity ? Or that there are at least 10 different strategies you can employ to dramatically cut data center energy consumption ? The fact is, most data centers are not designed with energy efficiency in mind. But in the white paper Implementing Energy-efficient Data Centers , you'll learn how to save money by using less electricity—whether your data centers are still in the design 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

data warehouse type  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...
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

data warehouse type  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...
Don't Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

data warehouse type  Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big 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

data warehouse type  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...
Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics
Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident

data warehouse type  and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are 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

data warehouse type  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...
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

data warehouse type  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. Read More...

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