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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 » etl data warehouse concepts


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

etl data warehouse concepts  data warehouse design. All ETL data warehouse processes were originally designed to be executed in batch mode, during previously scheduled downtimes. All operational data from distinct sources (e.g. ERP systems) was extracted, cleansed under a stage repository, and loaded into the data warehouse over long periods of time, mostly at night. These processes can take minutes or hours, depending on the volume of data being uploaded to the data warehouse. With the pressure to load more recent data into the Read More...
What Good Is Information If Nobody Sees It?
Keeping detailed historical information is a great idea in theory, but how can it be merged with current data to enable split-second decisions? Two companies

etl data warehouse concepts  Good Is Information If Nobody Sees It? What Good Is Information If Nobody Sees It? D. Geller and M. Reed - June 16, 2000 Event Summary Smith-Gardner builds and sells software products that pull together data from all of a company''s operational data channels. They recently announced a suite of products, collectively called Ecometry, which help online retailers collect and manage a wide range of customer and transaction data. The goal is to provide a single view of the customer data. Ecometry is Read More...
SAS/Warehouse 2.0 Goes Live
SAS Institute has announced the production availability of SAS/Warehouse Administrator software, Version 2.0. This new version provides IT the ability to

etl data warehouse concepts  extraction, transformation and loading (ETL) processes, Nauta said. By tracking the usage of information in the warehouse, IT staff can identify and remove data that is not being used. Removing unnecessary data makes the warehouse more efficient and maximizes hardware investments. Market Impact Publish/Subscribe metaphors are becoming much more common in the data warehouse arena. The ability for users to subscribe (request information on a regular basis), and for the server to publish ( push ) that Read More...
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

etl data warehouse concepts  via another set of ETL processes. It is in this layer data begins to take shape and it is not uncommon to have some end-user application access data from this layer especially if they are time sensitive, as data will become available here before it is transformed into the dimension / performance layer. Traditionally this layer is implemented in the Third Normal Form (3NF). Optimizing 3NF Optimizing a 3NF schema in Oracle requires the three Ps – Power, Partitioning and Parallel Execution. Power means Read More...
Oracle Warehouse Builder: Better Late than Never?
Close to a year behind schedule, Oracle released Warehouse Builder to the market. Oracle, in an interesting contradiction in terms, has stated that the product

etl data warehouse concepts  Warehouse Builder: Better Late than Never? Event Summary REDWOOD SHORES, Calif., Mar. 6, 2000 - Oracle announced the immediate availability of Oracle Warehouse Builder, an extensible and easy-to-use data warehouse design and deployment framework. As part of Oracle''s Intelligent WebHouse Initiative, Oracle Warehouse Builder automates much of the work that goes into creating a powerful, single data store for e-business analysis, specifically with its ability to integrate historical data with the Read More...
How Companies Use Data for Competitive Advantage
Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage.

etl data warehouse concepts  Companies Use Data for Competitive Advantage How Companies Use Data for Competitive Advantage Today, many businesses find they are under siege dealing with an explosion of data. Yet the best performing companies are mastering their data—and using it for competitive advantage. How are they able to accomplish this? What best practices, approaches, and technologies are they employing? Find out in Leveling the Playing Field: How Companies Use Data for Competitive Advantage . In this Economist Business Read More...
Deploying High-density Zones in a Low-density Data Center
New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center

etl data warehouse concepts  High-density Zones in a Low-density Data Center Deploying High-Density Zones in a Low-Density Data Center If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Together, APC’s global teams work to fulfill their mission of creating delighted customers. To do this, the Company focuses its efforts on four primary application areas: Home/Small Office; Business Networks; Data Centers and Facilities; and Access Provider Networks. Source 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

etl data warehouse concepts  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...
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

etl data warehouse concepts  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...
MSI Data


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2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

etl data warehouse concepts  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses Read More...
Warehouse Management Systems: Pie in the Sky or Floating Bakery?Part Two: The Pareto Principle, Processes, and People: Assessing Your Warehouse Management System Needs
To ensure your warehouse management system is implemented as painlessly as possible, you must assess your warehouse situation before you decide on a warehouse

etl data warehouse concepts  Management Systems: Pie in the Sky or Floating Bakery?Part Two: The Pareto Principle, Processes, and People: Assessing Your Warehouse Management System Needs Introduction After understanding the myths behind the claims of huge staff reductions , quick and easy implementation , and the fast and big return on investment, you need to know what type of features and functionality you should look for in a warehouse management system. The bells and whistles of a system might look enticing, but Read More...
10 Errors to Avoid When Building a Data Center
In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you''re going through the data center...

etl data warehouse concepts  Errors to Avoid When Building a Data Center Proper data center commissioning can help ensure the success of your data center design and build project. But it''s also a process that can go wrong in a number of different ways. In the white paper Ten Errors to Avoid when Commissioning a Data Center , find out which mistakes to avoid when you''re going through the data center commissioning process. From bringing in the commissioning agent too late into the process, to not identifying clear roles for Read More...
Six Steps to Manage Data Quality with SQL Server Integration Services
Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business

etl data warehouse concepts  Steps to Manage Data Quality with SQL Server Integration Services Melissa Data''s Data Quality Suite operates like a data quality firewall '' instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Six Steps to Manage Data Quality with SQL Server Integration Services : Data quality (Wikipedia) Six Steps to Manage Data Quality with SQL Server Integration Services Data Quality is also known as : Busin Read More...
A Roadmap to Data Migration Success
Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources,

etl data warehouse concepts  Roadmap to Data Migration Success Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them. Read More...

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