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Documents related to » data mart etl


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 mart etl  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration Read More...
A Road Map to Data Migration Success
Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project

data mart etl  a well-designed warehouse, one data mart will support multiple business units. Also, the data migration process is likely to be the initial load of an ongoing ETL process and there should be reuse of many components. Conduct a gap analysis. The features that the business expects from the target system may not have a data source at all, and the migration team may be the designated messenger to carry this bad news. For example, in an MDM customer data project, one region out of five has never captured 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 mart 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...
Ardent Software Enters the SAP Data Extraction Market
Ardent Software has announced the addition of SAP extraction and load capabilities to their DataStage product, increasing their strength in the Extract

data mart etl  Software Enters the SAP Data Extraction Market Event Summary Ardent Software, Incorporated of Westboro, Massachusetts (NASDAQ: ARDT) has announced support for extraction from SAP R/3 and also loading to SAP BW (Business Information Warehouse) using its DataStage Release 3.6. Ardent is referring to the new feature as the Packaged Application Connection Kit (PACK). With the DataStage Extract PACK for SAP R/3, users will be able to extract data directly from SAP R/3 systems natively and integrate it with Read More...
Computer Associates Splashes Into the Data Warehousing Market with Platinum Technology Acquisition
Computer Associates DecisionBase is an Extract/Transform/Load tool designed to help in the population and maintenance of data warehouses. First released in

data mart etl  management, or for smaller data mart implementations. Incomplete integration with ERP products also makes DecisionBase a poor candidate for customers who wish to extract data from SAP or PeopleSoft. Given its incomplete integration with mainframe data access products, DecisionBase may also not be the appropriate product for customers with a heavy reliance on legacy mainframe data sources (i.e. IMS, IDMS, and VSAM). Read More...
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but

data mart etl  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer 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 mart 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 Governance: Controlling Your Organization’s Mission-critical Information
Controlling your company’s key information through data governance is more than just good practice—it can make the difference between success and failure at

data mart etl  Information If you think data governance is something dry and remote, think again. When it comes to compliance, data governance can help your company avoid hefty fines and even jail terms for its senior executives. In terms of customer service, data governance can reduce customer churn while giving your company a decisive competitive edge. And as for supply chain management, data governance can help your company understand what products are selling, what products are in stock, and what products are on 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

data mart etl  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 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 mart 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...
Beware of Legacy Data - It Can Be Lethal
Legacy data can be lethal to your expensive new application – two case studies and some practical recommendations.

data mart etl  of Legacy Data - It Can Be Lethal Beware of Legacy Data It Can Be Lethal Featured Author - Jan Mulder - August 23, 2002 Introduction The term legacy is mostly used for applications. For example, according to the Foldoc dictionary, legacy is: A computer system or application program which continues to be used because of the cost of replacing or redesigning it and often despite its poor competitiveness and compatibility with modern equivalents. The implication is that the system is large, monolithic Read More...
Fundamentals of Managing the Data Center Life Cycle for Owners
Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and

data mart etl  of Managing the Data Center Life Cycle for Owners Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and o Read More...
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete

data mart etl  aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are 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 mart 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...
Six Steps to Manage Data Quality with SQL Server Integration Services
Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business

data mart etl  Steps to Manage Data Quality with SQL Server Integration Services Melissa Data''s Data Quality Suite operates like a data quality firewall '' instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Six Steps to Manage Data Quality with SQL Server Integration Services : Data quality (Wikipedia) Six Steps to Manage Data Quality with SQL Server Integration Services Data Quality is also known as : Read More...

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