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 etl data mining

Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

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Documents related to » etl data mining

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 environment. This article looks at issues in data quality and how they can be addressed.

etl data mining  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

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 technology selection and access to historical 'legacy' data are also discussed.

etl data mining  issue is whether the ETL tool moves all the data through its own engine on the way to the target, or can be a proxy and move the data directly from the source to the target. Selection of the business intelligence tool(s) requires decisions such as: Will multi-dimensional analysis be necessary, or does the organization need only generalized queries? Not all warehouse implementations require sophisticated analysis techniques such as data mining (statistical analysis to discover trends in the data), data Read More

Business Intelligence in SAP Environments


As a consequence of the acquisition of Business Objects, SAP has shifted its SAP business warehouse (BW) strategy to a more open data warehousing approach and is now focusing on the former Business Objects portfolio. This guide is designed to help existing SAP BW customers to plan to move to the new business intelligence (BI) environment, and outlines most important architecture options for a data warehouse strategy.

etl data mining  Intelligence in SAP Environments As a consequence of the acquisition of Business Objects, SAP has shifted its SAP business warehouse (BW) strategy to a more open data warehousing approach and is now focusing on the former Business Objects portfolio. This guide is designed to help existing SAP BW customers to plan to move to the new business intelligence (BI) environment, and outlines most important architecture options for a data warehouse strategy. 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 describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

etl data mining  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 performance management. These conferences supply a wealth of information aimed at improving organizational decision-making, optimizing performance, and achieving business objectives.

etl data mining  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

Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

etl data mining  Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data 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 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 Data can be a Big Deal - read this white paper for some useful tips on ensuring secure, quality data acquisition and management.

etl data mining  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 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? Read More

The Value of Big Data


As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value.

etl data mining  Value of Big Data As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value. Read More

Informatica PowerCenter 5 Enables Enterprise Data Integration


Informatica Corporation’s Informatica PowerCenter 5 is a platform for integrating data to be deployed in e-Business applications, analytic applications and data warehouses, including a wide range of data sources, from enterprise resource planning (ERP) systems such as SAP R/3 and PeopleSoft, to web logs and Siebel applications. Market validation of its offerings is shown in a record Q4 of 2000, with a 150% increase in revenue over the previous year.

etl data mining  PowerCenter 5 Enables Enterprise Data Integration Informatica PowerCenter 5 Enables Enterprise Data Integration M. Reed - April 5, 2001 Event Summary Informatica Corporation (NASDAQ: INFA), a provider of e-Business analytic software, has announced the availability of Informatica PowerCenter 5 , an enterprise data integration platform for the deployment and management of analytic applications and data warehouses. The vendor states that the Informatica PowerCenter 5 suite is designed to be a high Read More

Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses


Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more.

etl data mining  Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and Read More

Revamping Data Management: Big Data Proves Catalyst to Updating Data Management Strategies


Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain.

etl data mining  Data Management: Big Data Proves Catalyst to Updating Data Management Strategies Data management plays a key role in helping organizations make strategic sense of their data and how to best use it. Organizations with data management maturity have ushered in clear data goals, but many obstacles persist. This white paper reports survey results that help to establish a clear picture of how organizations are capitalizing on data management today, as well as what challenges and opportunities remain. 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 recovery requirements in order to support a wide range of applications, and to protect against a wide range of risk factors. Discover solutions that help organizations protect remote data and offer extensive data protection and recovery solutions for remote offices.

etl data mining  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 Read More

2012 Business Data Loss Survey results


This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now.

etl data mining  Business Data Loss Survey results This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now. Read More

New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

etl data mining  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More

Types of Prefabricated Modular Data Centers


Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

etl data mining  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More