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Documents related to » bi 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.

BI PERSPECTIVES ON DATA WAREHOUSING: 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 a result set back. Data Mining Tools: Tools that automatically search for patterns in data. These tools are usually driven by
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.

BI PERSPECTIVES ON DATA WAREHOUSING: open, published protocols for interoperability and integrated end-to-end data warehousing services. It utilizes technologies provided in Microsoft Office 2000 and Microsoft SQL Server 7.0 products, and a partnership with Data Warehousing Alliance members for complementary tools and applications. The DWF enables data warehousing solutions where the data comes from virtually any source and where any type of information can be delivered to any compliant client interface or application. Market Impact Once
12/1/1999

Business Process Overview: Warehousing Solutions
Business Process Overview: Warehousing Solutions. Search for Templates and Other Software to Delineate Your Evaluation Concerning the Business Process and Warehousing Solutions Warehousing processes are critical for the success of a distribution business. These processes are highly visible to your customers, and have a direct impact on their opinion of your company. If you cannot get the goods to your customers in the most efficient way, you risk losing their business. Your warehousing and logistics operations must translate into reliability and service.

BI PERSPECTIVES ON DATA WAREHOUSING: operations must translate into reliability and service. Business Process Overview: Warehousing Solutions style= border-width:0px; />   comments powered by Disqus Related Topics:   Supply Chain Management (SCM),   Warehouse Management System (WMS) Related Industries:   Merchant Wholesalers,   Durable Goods,   Transportation and Warehousing Source: IBS Learn more about IBS Readers who downloaded this white paper also read these popular documents! Extending BI’s Reach: Anticipate Outcomes,
11/16/2006 2:23:00 PM

Who Needs Warehousing Management and How Much Thereof?
The warehouse is no longer merely a static storage facility. It now has to use virtually real-time data to closely match supply to demand, eliminate the need to hold excess inventory, and increase the flow of goods throughout the supply chain.

BI PERSPECTIVES ON DATA WAREHOUSING: introduction an advanced kitting capability to a WMS product. Related to this is the order penetration point as the key variable in a logistics configuration. Introducing an advanced kitting capability is the apt answer from some best-of-breed WMS providers to help customers reduce the costs associated with their supply chains, where one of the most significant facilitators is manufacturing postponement . Kitting helps because it allows enterprises to keep their products in a more generic state as late
8/30/2005

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.

BI PERSPECTIVES ON DATA WAREHOUSING: 2013 Big Data Opportunities Survey 2013 Big Data Opportunities Survey Source: SAP Document Type: White Paper Description: 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
7/5/2013 2:25:00 PM

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, 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.

BI PERSPECTIVES ON DATA WAREHOUSING: The Value of Big Data The Value of Big Data Source: SAP Document Type: White Paper Description: 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. The Value of Big Data
8/8/2013 5:27:00 PM

EMC to Buy Data General
WALTHAM, Mass., August 9th, 1999 (Reuters) - High-end data storage leader EMC Corp. (NYSE:EMC) on Monday moved to grab a chunk of the mid-range storage business with a deal to buy Data General Corp. (NYSE:DGN) for $1.1 billion in stock, the companies said.

BI PERSPECTIVES ON DATA WAREHOUSING: Corp. (NYSE:DGN) for $1.1 billion in stock, the companies said. EMC, which holds a 35 percent share of the $12 billion high-end storage market, said it will lend its considerable distribution and support muscle to leverage Data General s CLARiiON line of mid-range storage systems. What this means: EMC strengthens its hold on the disk subsystem market in general EMC gains presence in the mid-range disk subsystem market (its present focus is the high end) EMC gains an entre into Dell s volumes (DG/Clariion
8/13/1999

Data Mining: The Brains Behind eCRM
Data mining has emerged from obscure beginnings in artificial intelligence to become a viable and increasingly popular tool for putting data to work. Data mining is a set of techniques for automating the exploration of data and uncovering hidden truths.

BI PERSPECTIVES ON DATA WAREHOUSING: User Recommendations Data mining capabilities can play an important role in successful customer relationship management. In evaluating a data mining package, users should ask in which category, supervised or unsupervised, it falls and whether it is suitable for their needs. For instance, insurance companies seeking to predict insurance fraud should consider packages that use unsupervised learning, as there are typically no baselines to serve as predictors. Consumer products retailers can use unsupervised
11/6/2000

Asset Data for Accurate Lifecycle Management
Among the areas where modern enterprise asset management (EAM) systems provide substantial benefits is the driving out of inefficiencies in business processes. This is why the development of effective maintenance policies is generally the foremost consideration for modern asset managers.

BI PERSPECTIVES ON DATA WAREHOUSING: executed with. The original reliability-centered maintenance (RCM) studies revealed that many routine tasks could actually contribute to failure, or to lower cost-effectiveness, by having limited or no impact on the performance of the asset (in effect wasting the maintenance budget). Executing these tasks with greater efficiency would have either have no impact at all on effectiveness, or would possibly even magnify the effects of unsuitable tasks. For example, after an RCM analyst had spent a lot of
8/24/2006

Data Grouping and Drill-down
Understanding process variation is vital—not only in manufacturing industries, but in transactional environments as well. That’s why the tools you use to understand the root cause of common cause variations need to be both powerful and easy to use, whether you’re measuring variations in sales performance, wait times in hospital emergency rooms, or cycle times for order fulfillment.

BI PERSPECTIVES ON DATA WAREHOUSING: White Papers: Business Intelligence (BI) |  Customer Relationship Management (CRM) |  Enterprise Resource Planning (ERP) |  Human Capital Management (HCM) |  Information Technology (IT) |  Key Performance Indicators (KPIs) |  Return on Investment (ROI) |  Software as a Service (SaaS) |  Total Cost of Ownership (TCO)
4/25/2007 10:47:00 AM

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.

BI PERSPECTIVES ON DATA WAREHOUSING: Modeling,   Business Intelligence (BI),   Data Cleansing Related Industries:   Management,   Scientific,   and Technical Consulting Services,   Management of Companies and Enterprises Related Keywords:   problem,   structure,   baseline,   Customer,   bad,   data Source: Baseline Consulting Learn more about Baseline Consulting Readers who downloaded this white paper also read these popular documents! Extending BI’s Reach: Anticipate Outcomes, Forecast Results, and Respond Proactively Best
5/25/2005 10:37:00 AM


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