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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...
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...
Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

etl data warehousing olap  extract, transform, and load (ETL) process in a data warehousing system extracts records from data source(s), transforms them using rules to convert data into a form that is suitable for reporting and analysis, and finally loads the transformed records into the destination (typically a data warehouse or data mart). Data cleansing is an integral part of the transformation process and enforces business and schema rules on each record and field. Data cleansing involves the application of quality screens 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...
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete

etl data warehousing olap  Center Projects: Advantages of Using a Reference Design It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and Read More...
Managing Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses
To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if

etl data warehousing olap  Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if managing IT is not your core competence, what are your options? A managed service provider (MSP) can help. Learn about the benefits of outsourcing data center management, and make sure your crucial business applications are always available Read More...
Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company

etl data warehousing olap  Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. 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 warehousing olap  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...
Data Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution
There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting

etl data warehousing olap  Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting firms across the globe willing to help you build them. However, it’s imperative for each data management solution to specialize to the unique needs of your organization’s business users, across varying functional areas. Read More...
Demystifying Data Science as a Service (DaaS)
With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been

etl data warehousing olap  Data Science as a Service (DaaS) With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white 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

etl data warehousing olap  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...
Data Pro Accounting Software
Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the

etl data warehousing olap  Pro Accounting Software Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX. Read More...
Data Quality Strategy: A Step-by-Step Approach
To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how

etl data warehousing olap  Quality Strategy: A Step-by-Step Approach To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality. Read More...

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