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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...
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...
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...
Comparing Business Intelligence and Data Integration Best-of-breed Vendors'' Extract Transform and Load Solutions
There are two types of extract transform and load (ETL) vendors. Business intelligence (BI) vendors integrate ETL functionality into their overall BI framework,

etl data warehousing olap  also the essence of ETL functionality. Data Integration Components In order to determine the most suitable ETL solution for them, organizations should evaluate their needs in terms of the core components of the data integration process, as listed below. Data Identification. What data does the organization need to extract and where does it come from? What end result, in terms of the data, does the organization want to analyze? Essentially, answering these questions means identifying the origin of the 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...
Tailoring SAP Data Management for Companies of All Sizes
The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are

etl data warehousing olap  SAP Data Management for Companies of All Sizes The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today''s environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management. 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...
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but

etl data warehousing olap  Data Quality: A Seven-step Plan for Any Size Organization 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 Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer 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...
Data Quality: Cost or Profit?
Data quality has direct consequences on a company''s bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and

etl data warehousing olap  Quality: Cost or Profit? Market Overview In the past year, TEC has published a number of articles about data quality. ( Poor Data Quality Means A Waste of Money ; The Hidden Role of Data Quality in E-Commerce Success ; and, Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics .) This time our focus takes us to the specific domain of data quality within the customer relationship management (CRM) arena and how applications such as Interaction from Interface Software can Read More...
Guidelines for Specification of Data Center Power Density
Conventional methods for specifying data center density don’t provide the guidance to assure predictable power and cooling performance for the latest IT

etl data warehousing olap  for Specification of Data Center Power Density Guidelines for Specification of Data Center Power Density 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 problems and temperature. Read More...
Transportation and Warehousing
The transportation industry moves goods in a number of ways: via land, ocean, or air. As the product is moved from location to final destination, successful

etl data warehousing olap  warehouse management system,warehousing,transportation,transportation management applications,tm software,tms software,warehouse management software, warehousing software,warehouse management systems wms,tms application,transportation management software,wms application,inventory software,inventory system,software comparison,selection,supply chain,project,supply chain managment,transportation management system,transport logistics,trasnportation sotfware,transport managment sytsem,selection process,transportation logistics,trucking softwares,logistics sotfware,warehousing solutions,distribution systems,logistics,warehousing managment,manufacturing,wms,supply chain,supply chain managment,application requirements,retail,stock control,performance evaluation,selection process,inventory management,distribution center,shipping sotfware. Read More...
Protecting Critical Data
The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data

etl data warehousing olap  Critical Data The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly. Read More...
The Data Explosion
RFID and wireless usage will drive up data transactions by ten fold over the next few years. It is likely that a significant readdressing of the infrastructure

etl data warehousing olap  Data Explosion Introduction Traffic on the World Wide Web continues to grow. Traffic on your S mall S mart F ast devices continues to grow. Ok, I admit it. I bought the cell phone that takes pictures. I didn''t know if it was useful; but being a technophile, I went for it. And rapidly it all came to me! I tried on a new cool jacket ... I crooned over it ... but for that much money, I wasn''t sure. Should I really buy this? Enter the pic in my cell phone! We chicks have our honor guard. You know those Read More...
Beware of Legacy Data - It Can Be Lethal
Legacy data can be lethal to your expensive new application – two case studies and some practical recommendations.

etl data warehousing olap  of Legacy Data - It Can Be Lethal Beware of Legacy Data It Can Be Lethal Featured Author - Jan Mulder - August 23, 2002 Introduction The term legacy is mostly used for applications. For example, according to the Foldoc dictionary, legacy is: A computer system or application program which continues to be used because of the cost of replacing or redesigning it and often despite its poor competitiveness and compatibility with modern equivalents. The implication is that the system is large, monolithic Read More...

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