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 olap data warehouse architecture

Browse RFP templates

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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 and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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Documents related to » olap data warehouse architecture

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 performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

olap data warehouse architecture  Warehousing , Data Warehousing OLAP , Resource Data Warehouse , Land and Resource Data Warehouse , Data Warehouse Web Site , Data Mining , Data Mart , Data Warehouse Architecture , Data Warehouse Concepts , Data Warehouse Tutorial , Data Warehouse Definition , OLAP , Business Intelligence , Huge Data Warehouse , Data Warehouse Appliance . NOTE: The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. Read More

The Data Warehouse Institute (TDWI) Conference in San Diego: The Agile Approach to Business Intelligence (BI)


Next month a TDWI World Conference will be taking place in San Diego, California. What’s so special about this conference anyway? The answer is simple:  the general topic is going to be “Creating an Agile BI Environment”. Progressively in the last four or five years, the agile software development methodology has been jumping from the software development area to the data warehouse

olap data warehouse architecture  and Technologies for Agile OLAP ” by John O´Brien, an expert in data architecture and analytics. •    “ Extreme Scoping: An Agile Approach to Data Warehousing and Business Intelligence ” given by Larissa Moss, an expert in the Data Warehouse field. Other Things to Look For As with all TDWI conferences, the San Diego World Conference will also have a broad coverage of topics from many aspects of the BI life cycle process—especially for data warehousing and data analysis. Here are some other Read More

Unlocking Hidden Value from Investments in SAP NetWeaver Business Warehouse


Extending the capabilities and value of SAP NetWeaver Business Warehouse is a concern for users. To improve data use and fact-based decision making, and reduce stranded spreadsheets, SAP users can choose a business intelligence (BI) software solution such as IBM Cognos 8, with budgeting, planning, and forecasting functions. Find out more about how you can improve your business performance management content with BI.

olap data warehouse architecture  transactional, warehoused, relational and OLAP as well as modern and ad-hoc sources through a single semantic layer, specifically a single, trusted semantic layer that enables data to be modeled once yet used everywhere. This capability avoids the need for migrating, transforming or modifying source data to ‘fit’ with the tool or use case at hand and therefore reduces the need for ongoing IT involvement and enhances decision effectiveness for business users. Specifically, as business context and 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 if your organization needs this type of IT solution.

olap data warehouse architecture  tools, online analytical processing (OLAP) analysis tools, data mining, forecasting, etc. Managers and decision makers realized that a data warehouse—and its technology—had the ability to provide a complete view of the status of an organization. But as operational systems evolved, businesses merged, and globalization augmented, the number of business transactions increased substantially. Soon it became clear that having only historical information available wouldn''t be enough to give companies all Read More

The Truth about Data Mining


It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be able to discover valuable data. Consequently, data mining technology becomes important. Here is a framework to help understand the data mining process.

olap data warehouse architecture  a certain time period. OLAP and data mining are frequently used in conjunction with each other, and we often find a happy coexistence of these two technologies in data warehousing and BI environments. Comparing statistics and data mining, on the other hand, is not as straightforward. A principal reason is that they belong to two separate branches of study—mathematics and computer science. While data mining involves exploring large amounts of data (gigabytes or terabytes) to discover otherwise hidden or 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 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 agile architectures that can confront the new challenges much easier.

olap data warehouse architecture  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

1010data Big Data Warehouse


Designed originally to solve Big Data analytics problems for companies like the New York Stock Exchange, the 1010data platform is a unique approach to data exploration. Built from scratch to deliver instant access to all the raw data in gigantic datasets, 1010data analytics offers a revolutionary a cloud-based platform that unifies data and analytics and provides a single repository for critical information assets.  

olap data warehouse architecture  Big Data Warehouse Designed originally to solve Big Data analytics problems for companies like the New York Stock Exchange, the 1010data platform is a unique approach to data exploration. Built from scratch to deliver instant access to all the raw data in gigantic datasets, 1010data analytics offers a revolutionary a cloud-based platform that unifies data and analytics and provides a single repository for critical information assets. 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 the risks and costs associated with these projects. This paper offers a handy checklist of issues to consider before, during, and after migration.

olap data warehouse architecture  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 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.

olap data warehouse architecture  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

Data Visualization: When Data Speaks Business


For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence for improving the data visualization and data delivery process.

olap data warehouse architecture  Visualization: When Data Speaks Business For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages 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.

olap data warehouse architecture  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

The New Virtual Data Centre


Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward.

olap data warehouse architecture  New Virtual Data Centre Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward. 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 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.

olap data warehouse architecture  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

Architecture Evolution: From Web-based to Service-oriented Architecture


Traditional enterprise systems have proven difficult to change and extend. The inherent problem of old core code and business logic duplication is part of the reason traditional enterprise resource planning systems have not readily taken to e-commerce.

olap data warehouse architecture  Evolution: From Web-based to Service-oriented Architecture Extending Applications to the Web Pre-Internet client/server technology relied on healthy communications between the machines involved, and local area networks (LANs) and wide area networks (WANs) became an expense and a management headache for most companies. Moreover, updating software versions, particularly on the numerous distributed personal computers (PCs), became an almost unsolvable problem. Many information technology (IT) 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 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.

olap data warehouse architecture  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