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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
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
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
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration

etl data warehousing olap  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More
Acumen Data Systems
Acumen Data Systems provides employee time and attendance systems and software. Its software@s focuses include job tracking, shop floor data collection, and

etl data warehousing olap  Data Systems Acumen Data Systems provides employee time and attendance systems and software. Its software’s focuses include job tracking, shop floor data collection, and employee scheduling. Read More
Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise
While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to

etl data warehousing olap  Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help. 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

etl data warehousing olap  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
Understanding the PCI Data Security Standard
The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a

etl data warehousing olap  the PCI Data Security Standard MessageLabs Hosted Web Security and Content Filtering service operates at the Internet level, intercepting viruses, and spyware. Source : MessageLabs | Now part of Symantec Resources Related to Understanding the PCI Data Security Standard : Payment Card Industry Data Security Standard (PCI DSS) (Wikipedia) Understanding the PCI Data Security Standard Data Security is also known as : Data Security Architecture , Data Security Articles , Data Security Audit , Read More
The Use of Ceiling-Ducted Air Containment in Data Centers
Ducting hot IT-equipment exhaust to a drop ceiling can be an effective air management strategy, improving the reliability and energy efficiency of a data center

etl data warehousing olap  Use of Ceiling-Ducted Air Containment in Data Centers Ducting hot IT-equipment exhaust to a drop ceiling can be an effective air management strategy, improving the reliability and energy efficiency of a data center. Typical approaches include ducting either individual racks or entire hot aisles and may be passive (ducting only) or active (include fans). This paper examines available ducting options and explains how such systems should be deployed and operated. Practical cooling limits are established Read More
Meet PCI DSS Compliance Requirements for Test Data with Data Masking
Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a

etl data warehousing olap  PCI DSS Compliance Requirements for Test Data with Data Masking Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more. Read More
An Architect''s Evaluation of Form and Function—the Dimensional Data Model
A detailed assessment and evaluation of data warehouse system functionality and how it applies to the dimensional data model using tools that the architect

etl data warehousing olap  Architect''s Evaluation of Form and Function—the Dimensional Data Model A detailed assessment and evaluation of data warehouse system functionality and how it applies to the dimensional data model using tools that the architect works with. Read More
Governance from the Ground Up: Launching Your Data Governance Initiative
Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing

etl data warehousing olap  from the Ground Up: Launching Your Data Governance Initiative Although most executives recognize that an organization’s data is corporate asset, few organizations how to manage it as such. The data conversation is changing from philosophical questioning to hard-core tactics for data governance initiatives. This paper describes the components of data governance that will inform the right strategy and give companies a way to determine where and how to begin their data governance journeys. 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

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