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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 mining etl  that are not obvious. Data mining is the process of discovering information from enterprise data that is otherwise hidden. For instance, an online bookstore suggests additional books based on what a user adds to his or her cart by examining evidence from other comparable buyers. This is done through the use of association rules applied to historical sales data. Although the primary purpose of mining data is to gain business insight, it can be applied to discover anomalies in data. Consider a Web-based 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

data mining etl  Warehouse Web Site , Data Mining , Data Mart , Data Warehouse Architecture , Data Warehouse Concepts , Data Warehouse Tutorial , Data Warehouse Definition , OLAP , Business Intelligence , Huge Data Warehouse , Data Warehouse Appliance . NOTE: The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in 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 mining etl  the industry, such as data mining or data integration. Leadership and Management The leadership and management track provided users with the insights needed to take a project from inception through to completion. Aside from identifying process and project management methodologies related to data warehousing and BI projects, emphasis was placed on the overall management of these projects. Ideas presented ranged from team building and the high level technical requirements needed to manage such projects, to Read More...
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 mining etl  a result set back. Data Mining Tools: Tools that automatically search for patterns in data. These tools are usually driven by complex statistical formulas. The easiest way to distinguish data mining from the various forms of OLAP is that OLAP can only answer questions you know to ask, data mining answers questions you didn''t necessarily know to ask. Data Visualization Tools: Tools that show graphical representations of data, including complex three-dimensional data pictures. The theory is that the user Read More...
The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding

data mining etl  analysis techniques such as data mining (statistical analysis to discover trends in the data), data visualization (graphical display of query results), or multi-dimensional analysis (the so called slice and dice ). Will the architecture be two-tiered or three-tiered? Three-tiered architectures offload some of the processing to an application server which sits between the database server and the end-user. Will the tool employ a push or a pull technology? ( Push technology publishes the queries to Read More...
The New Virtual Data Centre
Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business

data mining etl  New Virtual Data Centre Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward. Read More...
The Fast Path to Big Data
Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more

data mining etl  Fast Path to Big Data Today, most people acknowledge that big data is more than a fad and is a proven model for leveraging existing information sources to make smarter, more immediate decisions that result in better business outcomes. Big data has already been put in use by companies across vertical market segments to improve top- and bottom-line performance. As unstructured data becomes a pervasive source of business intelligence, big data will continue to play a more strategic role in enterprise 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

data mining etl  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...
Data Quality: A Survival Guide for Marketing
Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge

data mining etl  to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more. 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

data mining etl  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 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

data mining etl  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 and Read More...
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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

data mining etl  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 Software Read More...
Deploying High-density Zones in a Low-density Data Center
New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center

data mining etl  Zones in a Low-density Data Center Deploying High-Density Zones in a Low-Density Data Center If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Together, APC’s global teams work to fulfill their mission of creating delighted customers. To do this, the Company focuses its efforts on four primary application areas: Home/Small Office; Business Networks; Data Centers and Facilities; and Access Provider Networks. Source : APC Resources Read More...
Data Warehousing in the Big Data Era: Are You BIReady?
Netherlands-based BIReady automates the process of designing, deploying, and maintaining a data warehousing solution, allowing the optimization of all necessary

data mining etl  Warehousing in the Big Data Era: Are You BIReady? Netherlands-based BIReady automates the process of designing, deploying, and maintaining a data warehousing solution, allowing the optimization of all necessary BI and analytics tasks. Read this TEC product note from TEC senior BI and data management analyst Jorge Garcia to learn more about how BIReady is meeting its goal of helping companies become BI ready. Read More...

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