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Documents related to » etl data warehousing olap


A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing

etl data warehousing olap  are currently over 50 ETL tools on the market. The data acquisition phase can cost millions of dollars and take months or even years to complete. Data acquisition is then an ongoing, scheduled process, which is executed to keep the warehouse current to a pre-determined period in time, (i.e. the warehouse is refreshed monthly). Changed Data Capture: The periodic update of the warehouse from the transactional system(s) is complicated by the difficulty of identifying which records in the source have changed 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

etl data warehousing olap  differentiated from the conventional ETL tools for data warehousing because it neither moves data nor creates new data stores of integrated data. Rather, it leaves data where it is, leveraging metadata repositories across multiple foundation enterprise systems and visibly pulls information into new applications. As a result, customers may be content to trade-in expensive and pesky DWs for a data extraction and presentation layer that sits on top of existing transactional systems, but only on the 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

etl data warehousing olap  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...
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 warehousing olap  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...
A One-stop Event for Business Intelligence and Data Warehousing Information
The Data Warehousing Institute (TDWI) hosts quarterly World Conferences to help organizations involved in data warehousing, business intelligence, and

etl data warehousing olap  extract, transform, and load (ETL) development. It is important not to underestimate the importance of data integration, as the way data is integrated into a data warehouse or BI solution is the essence of that system. If a scorecard is developed to measure an organization''s sales metrics and the source data is not accurate, the key performance indicators (KPIs) set and reported on will be meaningless. Administration and Technology The administration and technology track identified and covered topics Read More...
Data Management Wish List: IT Is Open to Big Changes
Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and

etl data warehousing olap  Management Wish List: IT Is Open to Big Changes Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and consume the data. In recent years, however, information technology (IT) leaders have focused much more attention on their organizations’ data management platforms and capabilities. Download this white paper to get a better picture of the current data management landscape. 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 warehousing olap  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...
An Improved Architecture for High-efficiency, High-density Data Centers
Globally, data center power and cooling infrastructure wastes more than 60 million megawatt-hours per year that do not contribute usefully to powering IT

etl data warehousing olap  Improved Architecture for High-efficiency, High-density Data Centers An Improved Architecture for High-Efficiency, High-Density Data Centers If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. In today''s always on, always available world where businesses can''t stop and downtime is measured in dollars, American Power Conversion (APC) provides protection against some of the leading causes of downtime, data loss and hardware damage: power 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 warehousing olap  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 : 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 warehousing olap  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...
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

etl data warehousing 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...
New Data Protection Strategies
One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased

etl data warehousing olap  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More...
Automate to Optimize: The Foundation for Data Center Efficiency
IT administrators need to simplify both complex and routine tasks to deliver increasing value with limited resources. Data center automation can help minimize

etl data warehousing olap  to Optimize: The Foundation for Data Center Efficiency Automate to Optimize : The Foundation for Data Center Efficiency If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Today’s heterogeneous enterprise data center environments are quickly growing in size and complexity, driven by mergers and acquisitions, expansion into multiple data centers, and large-scale initiatives such as server and storage consolidation. Source : Tidal S Read More...

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