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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

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...
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 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...
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

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...
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 mining  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...
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

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...
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

etl data mining  High-density 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 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 mining  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. BEGINLYX Read More...
Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization
Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as

etl data mining  think Data Integration: Delivering Agile BI Systems with Data Virtualization Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more Read More...
Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a

etl data mining  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization''s customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. 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

etl data mining  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...
IFS Applications (version 8.0) for ERP for the Mining Industry Certification Report
IFS Applications (v. 8.0) is TEC Certified for online evaluation of enterprise resource planning (ERP) solutions for the mining industry in the ERP Evaluation

etl data mining  IFS Applications,IFS Applications v.8.0,IFS Applications ERP for the mining industry,IFS Applications ERP software for mining,ERP software for the mining industry,ERP solution for the mining industry,IFS ERP software for the mining industry,IFS ERP solution for the mining industry,IFS Read More...
Linked Enterprise Data: Data at the heart of the company
The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet

etl data mining  Enterprise Data: Data at the heart of the company The data silos of today''s business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, bre Read More...
Big Data Comes of Age: Shifting to a Real-time Data Platform
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving

etl data mining  Data Comes of Age: Shifting to a Real-time Data Platform New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a Read More...
Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever
Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online

etl data mining  Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility. Read More...

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