Data Warehouse Automation ILM: Related Documents

Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

DATA WAREHOUSE AUTOMATION ILM: Six Steps to Manage Data Quality with SQL Server Integration Services Six Steps to Manage Data Quality with SQL Server Integration Services Source: Melissa Data Document Type: White Paper Description: Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in
9/9/2009 2:32:00 PM

Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g for Data Warehousing and Business Intelligence. Find RFP Templates and Other Solutions to Define Your Project In Relation To Oracle Database, Data Warehousing and Business Intelligence. Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

DATA WAREHOUSE AUTOMATION ILM: how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Oracle Database 11g for Data Warehousing and Business Intelligence style= border-width:0px; /> comments powered by Disqus Related Topics: Business Intelligence and Data Management, Business Intelligence (BI), Data Mining, Data Warehouse, End-User Query and Reporting, Data Mart Source: Oracle Learn more about Oracle Readers who
4/20/2009 3:11:00 PM

Developing a Universal Approach to Cleansing Customer and Product Data
Developing a Universal Approach to Cleansing Customer and Product Data. Find Free Proposal and Other Solutions to Define Your Acquisition In Relation To Cleansing Customer and Product Data. Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

DATA WAREHOUSE AUTOMATION ILM: Cleansing Customer and Product Data Developing a Universal Approach to Cleansing Customer and Product Data Source: SAP Document Type: White Paper Description: Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy,
6/1/2009 5:10:00 PM

Achieving a Successful Data Migration
Achieving a Successful Data Migration. Solutions and Other Software to Delineate Your System and for Achieving a Successful Data Migration. The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

DATA WAREHOUSE AUTOMATION ILM: Achieving a Successful Data Migration Achieving a Successful Data Migration Source: Informatica Document Type: White Paper Description: The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.
10/27/2006 4:30:00 PM

The Modern Virtualized Data Center
Data center resources are often underused while drawing enormous amounts of power and taking up valuable floor space. Virtualization has been a positive evolutionary step in the data center, driving consolidation of resources to maximize power saving and to simplify management and maintenance. Learn more about the benefits of virtualization, and the issues you need to consider when planning a consolidation project.

DATA WAREHOUSE AUTOMATION ILM: The Modern Virtualized Data Center The Modern Virtualized Data Center Source: Pillar Data Systems Document Type: White Paper Description: Data center resources are often underused while drawing enormous amounts of power and taking up valuable floor space. Virtualization has been a positive evolutionary step in the data center, driving consolidation of resources to maximize power saving and to simplify management and maintenance. Learn more about the benefits of virtualization, and the issues you need to
8/15/2008 2:38:00 PM

Six Misconceptions about Data Migration
A truly successful data migration project involves not only an understanding of how to migrate the data from a technical standpoint, but an understanding of how that data will be used and its importance to the operation of the enterprise.

DATA WAREHOUSE AUTOMATION ILM: Six Misconceptions about Data Migration Six Misconceptions about Data Migration Norma L. Davis - June 23, 2008 Read Comments Originally published February 4th, 2008 As organizations embark on a system implementation, one of the most important and riskiest activities is data migration—the movement of data from the old legacy system to the new system. While the selection, implementation, and operation of an enterprise application for enterprise resource planning (ERP), enterprise asset management (EAM),
6/23/2008

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 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 information technology (IT). Companies that recognize this reality—and that act on it in a technologically, operationally, and economically optimized way—will gain sustainable competitive advantages.

DATA WAREHOUSE AUTOMATION ILM: Fast Path to Big Data The Fast Path to Big Data Source: Wipro Technologies Document Type: White Paper Description: 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
2/7/2013 12:55:00 AM

Data Quality Strategy: A Step-by-Step Approach
To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

DATA WAREHOUSE AUTOMATION ILM: Data Quality Strategy: A Step-by-Step Approach Data Quality Strategy: A Step-by-Step Approach Source: SAP Document Type: White Paper Description: To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP
3/16/2011 2:03:00 PM

Data Mart Calculator
Need a model to help calculate an estimate of manpower needs by role, timeline, and labor cost to build a data mart based on user-supplied variables? Here’s a calculator that provides two estimates. The first is based on using the traditional “develop by committee,” and the second on developing the same data mart at the developmental level. The model needs minimal input and can be changed to fit your needs. Find out more.

DATA WAREHOUSE AUTOMATION ILM: Data Mart Calculator Data Mart Calculator Source: Glenridge Solutions LLC Document Type: White Paper Description: Need a model to help calculate an estimate of manpower needs by role, timeline, and labor cost to build a data mart based on user-supplied variables? Here’s a calculator that provides two estimates. The first is based on using the traditional “develop by committee,” and the second on developing the same data mart at the developmental level. The model needs minimal input and can be
5/22/2009 11:18:00 AM

Microsoft says OLE for Data Mining: Is it Bull?
Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.

DATA WAREHOUSE AUTOMATION ILM: mining solutions for their data warehouse should investigate PMML and its potential for widespread acceptance. OLE DB is a proprietary Microsoft standard, which conflicts with standards from bodies such as the OMG (Object Management Group). Customers should be wary of this new standard and make sure that it interacts effectively with other database and business intelligence products they are considering. However, existing Microsoft customers may be able to leverage this technology in a short timeframe.
3/28/2000

Data Storage in the Cloud—Can you Afford Not To?
Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

DATA WAREHOUSE AUTOMATION ILM: Data Storage in the Cloud—Can you Afford Not To? Data Storage in the Cloud—Can you Afford Not To? Source: Riverbed Technology Document Type: White Paper Description: Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or
7/12/2011 2:19:00 PM

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