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Documents related to » olap perspectives on data warehousing


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 describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

OLAP PERSPECTIVES ON DATA WAREHOUSING: Analytical Processing (OLAP), Relational OLAP (ROLAP), Multi-Dimensional OLAP (MOLAP), Hybrid OLAP (HOLAP, a combination of MOLAP and ROLAP), and more. BI can be broken down into four broad fields: Multi-dimensional Analysis Tools: Tools that allow the user to look at the data from a number of different angles . These tools often use a multi-dimensional database referred to as a cube . Query tools: Tools that allow the user to issue SQL (Structured Query Language) queries against the warehouse and get
8/18/2002

Microsoft Goes Their Own Way with Data Warehousing Alliance 2000
Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 vendors throughout the industry have qualified for Microsoft« Data Warehousing Alliance 2000. Alliance members and partners are committed to delivering tools and applications based on the Microsoft Data Warehousing Framework 2000, an open architecture based on the open standards and services built into the Windows« 2000 operating system, Microsoft SQL Server 7.0 and Office 2000.

OLAP PERSPECTIVES ON DATA WAREHOUSING: microsoft data warehousing, olap software, data warehouse applications, power olap, data warehouse software, open source data warehousing, data warehouse vendors, data warehouse appliance, data warehouse education, data warehousing software, data warehouse products, data mining articles, data warehouse tools, data integration tools, bi strategy, data extraction, data warehouse training, data warehousing tools, olap open source, real time data warehouse, data warehousing jobs, the data warehouse lifecycle toolkit, open source etl, data warehousing training, datawarehouse architecture, data .
12/1/1999

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.

OLAP PERSPECTIVES ON DATA WAREHOUSING:
9/9/2009 2:32:00 PM

The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

OLAP PERSPECTIVES ON DATA WAREHOUSING: etl data, data warehouse etl, etl software, data warehousing etl, etl technology, etl solutions, extract transform load, data integration, etl system, intranet software, etl process, the data warehousing institute, data warehouse and business intelligence, data warehousing and business intelligence, data warehouse training, open source data warehousing, data warehousing software, data warehouse education, data warehouse products, data warehouse best practices, real time data warehouse, data warehousing books, data architecture, data warehousing basics, data warehouse security, enterprise data .
8/2/2000

Why Systems Fail - The Dead-end of Dirty Data
If your data does not reflect reality, the system can never be effective. In today’s world of collaboration, showing a trading partner dirty data is giving them the wrong message and tearing down the trust called for in a collaborating partnership.

OLAP PERSPECTIVES ON DATA WAREHOUSING:
7/4/2003

The Bottom Line on Bad Customer Data
You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no wonder the complaint resolution pipeline is backed up. Think it’s your customer resource management (CRM) system? Think again. It’s bad data, and it’s costing you millions. Request your copy of The Bottom Line on Bad Customer Data that delivers detailed advice from Jill Dyche, partner and co-founder of Baseline Consulting, about what you can do to address the impact of bad data on your company. The report gives you insight into how bad data is impacting your company and what you can do about it. How to identify where the bad data is and quantify its impact, and different approaches to determine the sources and causes of bad data are all offered in this paper.

OLAP PERSPECTIVES ON DATA WAREHOUSING: problem, structure, baseline, Customer, bad, data.
5/25/2005 10:37:00 AM

Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio » The TEC Blog
memory , Kognitio , OLAP , pablo , Roger Gaskell , wx2 Comments Irving on 24 March, 2012 at 8:45 pm # Radical thinking about data warehousing is an innovative way in data preservation. The idea is to keep records and info of all sorts be protected and still can be accessed in the years to come. And that’s just what Roger Gaskell emphasized in this interview. Good one! Irving My Blog: armoire penderie pour enfant   * Name: * E-mail (private) : Web site: XHTML: You can use these tags: --> * Comments: *

OLAP PERSPECTIVES ON DATA WAREHOUSING: analytics, big data, data bases, data warehouse, edw, in memory, Kognitio, OLAP, pablo, Roger Gaskell, wx2, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
12-12-2011

Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be gained from analysis of such big data are immense, so are the inherent challenges, including need for rapid analysis. In his article, TEC BI analyst Jorge García discusses how in-memory analytics helps address these challenges and reap the benefits hidden in big data.

OLAP PERSPECTIVES ON DATA WAREHOUSING: data stored in RAM, OLAP applications can speed the data query and analysis process as well as ease data modeling by applying innovative ways for organizing and storing data. The table below lists some software products that use in-memory technologies for OLAP services.   Product Vendor PowerPivot Microsoft Cognos TM1 IBM Jedox OLAP Accelerator (GPU) Jedox WebFOCUS Visual Discovery Information Builders BIRT Data Objects and BIRT Data Analyzer Actuate Tableau Tableau Software Many products already
3/20/2012 10:25:00 AM

Managing the Tidal Wave of Data
Despite the slowing economy, data growth continues due to the digitization of infrastructures, the need to keep more copies of data for longer periods, and the rapid increase in distributed data sources. This data growth creates a wide range of management challenges. Discover solutions that can help your company maximize its storage environment and reduce costs while improving service and managing risks.

OLAP PERSPECTIVES ON DATA WAREHOUSING: IBM, san, storage, storage devices, virtualization, media storage, data storage, device storage, disk storage, hp storage, network attached storage, server storage, storage manager, storage server, san design, san management, san storage, nas storage, hp san, server virtualization, storage management, virtualization server, raid storage, storage area network, san network, san server, san technology, scsi storage, virtualization software, virtualization technology, emc storage, san nas, storage array, emc san, iscsi san, iscsi storage, storage virtualization, virtual storage, ip san, esx .
4/29/2010 4:04:00 PM

2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unispere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses and a discussion of the results.

OLAP PERSPECTIVES ON DATA WAREHOUSING: big data, analytics, Unisphere Research, big data survey, data manager survey, big data challenges, big data initiatives.
7/5/2013 2:25:00 PM

Poor Data Quality Means A Waste of Money
Data quality sounds like a motherhood and apple pie issue, of course we want our data to be right. However, very few enterprises get serious about it. Maybe that's because the cost of data quality is hidden. That cost can be huge.

OLAP PERSPECTIVES ON DATA WAREHOUSING:
9/23/2003


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