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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 olap


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 olap  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 olap  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...
Attaining Real Time, On-demand Information Data: Contemporary Business Intelligence Tools
Demand for instant access to dispersed information is being met by vendors offering enterprise business intelligence tools and suites. Portlet standardization

implementing data warehouse olap  feel somewhat better about implementing cumbersome ERP and other enterprise systems. Indeed, many enterprises have already deployed some BI products too, such as querying and reporting tools, planning and budgeting applications, analytic applications, incentive management systems, portals, dashboards, and scorecards, along with data warehousing technology, data models, and integration software, and whatnot. In fact, anyone stocktaking technology inventory will likely find some CPM components already in Read More...
Business Intelligence Success, Lessons Learned
Is business intelligence (BI) an application that pays off? We have all heard mixed results but a 2003 extensive study on on-line analytical processing (OLAP

implementing data warehouse olap  19 percent of companies implementing BI claim they have met or exceeded their business goals. Over 60 percent state they have at least largely met their goals. As always, soft benefits were more easily obtainable than hard benefits. A detailed look at the types of benefits reveals the following: Benefit % Companies Realizing Benefit Faster, more accurate reporting 81 Improved decision making 78 Improved customer service 56 Increased revenue 49 Savings in non-IT costs 50 IT savings 40 When the statistics Read More...
Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio
Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the

implementing data warehouse olap  is no overhead of implementing a data warehouse onsite, and there is no need for an information technology (IT) department to service, maintain, and support the database. Instead, organizations can focus on meeting their business goals, and not get bogged down with infrastructure issues. The challenge is always getting access to the data in the underlying source systems and deciding the type of cloud model that best suits the company. Is it ok to run analytic projects in the public cloud or would it be Read More...
Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization
Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as

implementing data warehouse olap  think Data Integration: Delivering Agile BI Systems with Data Virtualization Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more 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 olap  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...
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

implementing data warehouse olap  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...
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

implementing data warehouse olap  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 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

implementing data warehouse olap  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...
Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting

implementing data warehouse olap  Integration: Creating a Trustworthy Data Foundation for Business Intelligence Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting requirements. This paper discusses the importance of data integration and helps you identify key challenges of integrating data. It also provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data. BEGINL 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

implementing data warehouse olap  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

implementing data warehouse olap  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 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? Read More...
A Solution to Data Capture and Data Processing Challenges
Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the

implementing data warehouse olap  Solution to Data Capture and Data Processing Challenges Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems. 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 olap  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...

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