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Documents related to » data warehousing olap etl


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 warehousing olap 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...
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 warehousing olap etl  When embarking on a data warehousing or business intelligence project, it is essential for organizations to emphasize the quality of data that is used for analysis and subsequent decision making. As data captured from a multitude of sources makes its way to an enterprise data warehouse or data marts, a data quality framework creates a screening process that measures the purity of the data and corrects any inconsistencies found. This article walks the reader through a typical data quality strategy by 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 warehousing olap etl  Data Warehouse Concepts , Data Warehousing Information Center , Data Integration Paper , Data Warehouse Software , Data Warehousing Analysis , Data Warehouse Community , Data Warehouse Automation , Perspectives on Data Warehousing , Data Warehousing OLAP , Resource Data Warehouse , Land and Resource Data Warehouse , Data Warehouse Web Site , Data Mining , Data Mart , Data Warehouse Architecture , Data Warehouse Concepts , Data Warehouse Tutorial , Data Warehouse Definition , OLAP , Business Intelligence Read More...
Comparing Business Intelligence and Data Integration Best-of-breed Vendors'' Extract Transform and Load Solutions
There are two types of extract transform and load (ETL) vendors. Business intelligence (BI) vendors integrate ETL functionality into their overall BI framework,

data warehousing olap etl  2000 to extend its data warehousing capabilities, provides a product called dfPowerStudio that can identify data accuracy, validity, and patterns to standardize data. Moreover, dfPowerStudio can monitor and audit data by providing alerts to identify the state of organizational data over time. Alerts are also provided to identify data quality levels and business rule violations. Additionally, dfPowerStudio analyzes and corrects data inconsistencies. It matches data by clustering data into groups, merging Read More...
The Evolution of a Real-time Data Warehouse
Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine

data warehousing olap etl  of products for deploying data warehousing solutions, such as Exadata Storage Server (based on the HP ProLiant DL180 G5 server), HP Oracle Database Machine designed for multiterabyte data warehouses, and the Oracle Warehouse Builder integration tool that supports advanced data loads and data capture for low latency databases. They also offer other products like Oracle Partitioning, which can lower query times and increase data availability. Teradata Among other products offered, Terada Database 12 is an Read More...
An Architect''s Evaluation of Form and Function—the Dimensional Data Model
A detailed assessment and evaluation of data warehouse system functionality and how it applies to the dimensional data model using tools that the architect

data warehousing olap etl  Form and Function—the Dimensional Data Model A detailed assessment and evaluation of data warehouse system functionality and how it applies to the dimensional data model using tools that the architect works with. Read More...
Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security
Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all

data warehousing olap etl  Best Practices in Application Data Security Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace. 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

data warehousing olap etl  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. 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 warehousing olap 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...
Enterprise Data Management: Migration without Migraines
Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an

data warehousing olap etl  Data Management: Migration without Migraines Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more. Read More...
Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices
This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions

data warehousing olap etl  up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information Read More...
Data Management Wish List: IT Is Open to Big Changes
Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and

data warehousing olap etl  Open to Big Changes Data management, access, and analysis haven’t always received the same amount of consideration, or respect, as the corporate applications that generate and consume the data. In recent years, however, information technology (IT) leaders have focused much more attention on their organizations’ data management platforms and capabilities. Download this white paper to get a better picture of the current data management landscape. Read More...
Garbage in, Garbage out: Getting Good Data out of Your BI Systems
Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems.

data warehousing olap etl  Garbage out: Getting Good Data out of Your BI Systems Garbage in, garbage out. Poor quality data leads to bad business decisions. You need high quality data in your business intelligence (BI) system to facilitate effective analysis—to make the right decisions at the right time. But how do you achieve this? Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems . In this Focus Brief , you''ll learn about the steps in the data delivery cycle, the problems can occur at each step, Read More...
Data Storage in the Cloud--Can You Afford Not To?
In Data Storage in the Cloud Can You Afford Not To?

data warehousing olap etl  Afford Not To? Spiraling data storage requirements are straining many companies'' abilities to keep pace. One obvious solution is storage in the cloud—but concerns regarding security, speed, and accessibility remain. Or do they? In Data Storage in the Cloud—Can You Afford Not To? , you''ll discover a cloud storage solution that offers you high-security dual-level encryption (SSLv3 and 256-bit AES) data accessibility from anywhere lower costs due to the economies of scale of cloud storage providers high 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

data warehousing olap etl  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...

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