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Documents related to » data warehousing olap etl


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

data warehousing olap etl  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing 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

data warehousing olap etl  for Business Intelligence and Data Warehousing Information The Data Warehousing Institute ( TDWI ) hosts its quarterly World Conference in cities across the US to help organizations involved in data warehousing, business intelligence (BI), and performance management, by giving them access to industry experts, and providing impartial classes related to topics pertinent to the industry. As the industry grows, organizations are faced with questions about how to best access their data to drive profits and 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,

data warehousing olap etl  2000 to extend its data warehousing capabilities, provides a product called dfPowerStudio that can identify data accuracy, validity, and patterns to standardize data. Moreover, dfPowerStudio can monitor and audit data by providing alerts to identify the state of organizational data over time. Alerts are also provided to identify data quality levels and business rule violations. Additionally, dfPowerStudio analyzes and corrects data inconsistencies. It matches data by clustering data into groups, merging 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

data warehousing olap etl  two or more applications. Data warehousing whereby data is extracted from a variety of data sources and channeled into a specific database or DW for analysis. Common virtual system , which would be the peak of EAI, whereby all aspects of enterprise computing are tied together so that they appear as a unified application. EII is also 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 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

data warehousing olap etl  When embarking on a data warehousing or business intelligence project, it is essential for organizations to emphasize the quality of data that is used for analysis and subsequent decision making. As data captured from a multitude of sources makes its way to an enterprise data warehouse or data marts, a data quality framework creates a screening process that measures the purity of the data and corrects any inconsistencies found. This article walks the reader through a typical data quality strategy by 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

data warehousing olap etl  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...
Addressing the Complexities of Remote Data Protection
As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and

data warehousing olap etl  the Complexities of Remote Data Protection Because data protection is a concern for organizations of all sizes, IBM offers remote data protection for the enterprise, as well. This high performance and easy-to-use service delivers consistent and cost-effective data protection without increased network investment. Source: IBM Resources Related to Addressing the Complexities of Remote Data Protection : Continuous Data Protection (CDP) (Wikipedia) Addressing the Complexities of Remote Data Protection Read More...
Data Quality Basics
Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at

data warehousing olap etl  Quality Basics Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue. Read More...
Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence
Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting

data warehousing olap etl  provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data. 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

data warehousing olap etl  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...
Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

data warehousing olap etl  Masking: Strengthening Data Privacy and Security Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you. Read More...
Next-generation Data Auditing for Data Breach Protection and Risk Mitigation
Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation

data warehousing olap etl  generation Data Auditing for Data Breach Protection and Risk Mitigation Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system. 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

data warehousing olap etl  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 help reduce the negative impact that poor data quality has on a CRM objective. Read More...
Don''t Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

data warehousing olap etl  Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Read More...

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