Home
 > search for

Featured Documents related to » define data warehouse



ad
Get Free BPM Software Comparisons

Find the best BPM software solution for your business!

Use the software selection tool employed by IT professionals in thousands of selection projects per year. FREE software comparisons based on your organization's unique needs—quickly and easily!
Register to access your free comparison reports and more!

Country:

 Security code
Already have a TEC account? Sign in here.

Documents related to » define data warehouse


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.

DEFINE DATA WAREHOUSE: Identifiers — These identifiers define a business entity s master system of record. As you bring together data from various data sources, an organization must have a consistent mechanism to uniquely identify, match, and link customer information across different business functions. While data connectivity provides the mechanism to access master data from various source systems, it is the Total Data Quality process that ensures integration with a high level of data quality and consistency. Once an
9/9/2009 2:32:00 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.

DEFINE DATA WAREHOUSE: set of validation rules defined in the target application, the data load will fail. Bad data in the target application can impact business processes after a go-live and necessitate costly manual fixes. Organizations must establish user confidence in the data. In order to fully trust data, business users want the ability to trace it, to find out where it came from and how it was changed. This requires some form of data lineage capability, such as metadata management. Data profiling, validation, and
10/27/2006 4:30:00 PM

Four Critical Success Factors to Cleansing Data
Four Critical Success Factors to Cleansing Data. Find Guides, Case Studies, and Other Resources Linked to Four Critical Success Factors to Cleansing Data. Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

DEFINE DATA WAREHOUSE: and Business Owners who define what is needed. If you have internal data tools already implemented, then use them. If you don t, then don t run out and buy one just for this project. Implementing a PIM or PDM, is a whole separate project. Most vendors will only import clean data, so you still have to do the hard work first. Not to worry, most any technical analyst can link to tables via ODBC and extract out the data needed for analysis. Most data cleansing vendors have built their own proprietary tools
1/14/2006 9:29:00 AM

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.

DEFINE DATA WAREHOUSE: capability for DBA’s to define custom partitioning schemes; a rich set of adminstrative commands for partitioned tables; and a partition adviser to guide administrators on how best to implement partition. Partitioning also enables ILM ( Information Lifecycle Management ) strategies within the Oracle database. A single table, when partitioned, can be distributed across multiple storage tiers. Old, less-frequently accessed data, corresponding to older partitions, can be stored on less expensive storage
4/20/2009 3:11:00 PM

3 Big Trends in Data Visualization » The TEC Blog
3 Big Trends in Data Visualization » The TEC Blog TEC Blog     TEC Home     About TEC     Contact Us     About the Bloggers     Follow TEC on Twitter    RSS   Discussing Enterprise Software and Selection --> Fast, Accurate Software Evaluations TEC helps enterprises evaluate and select software solutions that meet their exacting needs by empowering purchasers with the tools, research, and expertise to make an ideal decision. Your software selection starts here. Learn more about TEC s

DEFINE DATA WAREHOUSE: TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
15-12-2011

Best Practices for a Data Warehouse on Oracle Database 11g
Best Practices for a Data Warehouse on Oracle Database 11g. Find Out Software and Other Solutions for Your Decision Associated with Best Practices and Data Warehouse Management. 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 performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

DEFINE DATA WAREHOUSE: It allows you to define the types of information needed in the data warehouse to answer the business questions and the logical relationships between different parts of the information. It should be simple, easily understood and have no regard for the physical database, the hardware that will be used to run the system or the tools that end users will use to access it. There are two classic models used for data warehouse, Third Normal Form and dimensional or Star Schema. Third Normal Form (3NF) is a
4/20/2009 3:11:00 PM

Information Life Cycle Management for Business Data
Information Life Cycle Management for Business Data. Find RFP Templates and Other Solutions to Define Your Acquisition In Relation To Information Life Cycle Management. While companies have long seen their stores of data as valuable corporate assets, how they manage those stores varies enormously. Today, however, new government regulations require that companies retain and control information for long periods of time. Find out what IT managers are doing to meet these new regulatory requirements, and learn about solutions for storing vast quantities of data for the lowest possible cost.

DEFINE DATA WAREHOUSE: Steps Step 1 - Define the Data Classes Step 2 – Create Storage Tiers for the Data Classes The Costs Savings of using Tiered Storage Assigning Classes to Storage Tiers Step 3 – Create Data Access and Migration Policies Managing Access to Data Migrate Data between Classes Regulatory Compliance Step 4 – Define and Enforce Compliance Policies Oracle ILM Assistant The Benefits of an Online Archive Conclusion INTRODUCTION Although most organizations have long regarded their stores of data as one of their
4/20/2009 3:12:00 PM

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.

DEFINE DATA WAREHOUSE: The 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

The Data Explosion
RFID and wireless usage will drive up data transactions by ten fold over the next few years. It is likely that a significant readdressing of the infrastructure will be required--in the enterprise and the global bandwidth.

DEFINE DATA WAREHOUSE: The Data Explosion The Data Explosion Ann Grackin - October 20, 2004 Read Comments Introduction Traffic on the World Wide Web continues to grow. Traffic on your S mall S mart F ast devices continues to grow. Ok, I admit it. I bought the cell phone that takes pictures. I didn t know if it was useful; but being a technophile, I went for it. And rapidly it all came to me! I tried on a new cool jacket ... I crooned over it ... but for that much money, I wasn t sure. Should I really buy this? Enter the pic in
10/20/2004

Metagenix Reverse Engineers Data Into Information
Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an

DEFINE DATA WAREHOUSE: Metagenix Reverse Engineers Data Into Information Metagenix Reverse Engineers Data Into Information M. Reed - February 15, 2001 Read Comments M. Reed - February 15, 2001 Event Summary Metagenix, Inc. has designed its flagship product, MetaRecon to, as they put it, Decipher Your Data Genome . The product reverse engineers all of the metadata ( data about data ) from data sources and generates information that is very helpful to developers in designing specifications for a new data store, and assists
2/15/2001

Logs: Data Warehouse Style
Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency.

DEFINE DATA WAREHOUSE: Logs: Data Warehouse Style Logs: Data Warehouse Style Source: LogLogic Document Type: White Paper Description: Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled
2/8/2008 1:14:00 PM


Recent Searches
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Others