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Documents related to » data model complexity


Complexity, Decision Making, and Big Data
The technology market is giving significant attention to big data and analytics as a way to provide insight for decision support, but how far along is the adoption of these technologies across manufacturing organizations? This white paper looks at the results of a 2013 survey by Aberdeen examining the analytics and big data activities of manufacturers, Including time-sensitive, complex decision making and decision making challenges and capabilities.

DATA MODEL COMPLEXITY: Decision Making, and Big Data Complexity, Decision Making, and Big Data Source: SAP Document Type: White Paper Description: The technology market is giving significant attention to big data and analytics as a way to provide insight for decision support, but how far along is the adoption of these technologies across manufacturing organizations? This white paper looks at the results of a 2013 survey by Aberdeen examining the analytics and big data activities of manufacturers, Including time-sensitive,
8/8/2013 10:07:00 AM

Differences in Complexity between B2C and B2B E-commerce
Business-to-business (B2B) selling has proven to be more intricate than business-to-consumer (B2C) selling, as B2B involves dealing with longer-term contracts and complex products with specific requirements that are not needed in the consumer world.

DATA MODEL COMPLEXITY: because of all the data involved, B2B transactions and interactions are more complex than those in B2C, which tend to be very standardized and typically without a lot of custom pricing and listings of available parts. Thus, a mere window dressing of B2C platforms has not worked for complex B2B requirements like the following: Contract management—i.e., instead of a mere spot-sourcing that gives a flat retail price for every item sold in B2C model, the B2B world rotates around the direct-sourcing model,
11/6/2004

Dealing with Global Trade Management Complexity
To optimally complete the global trade cycle, a business must automate, track, and provide visibility to the entire global trade management process to optimize its supply and distribution chains.

DATA MODEL COMPLEXITY: want its ERP master data going directly to vendors. It is far more secure to have a system that takes only the absolute necessary data from the ERP or back-office system to share with the supplier. In the case of TradeBeam, the company has been striving to distinguish itself from peers and competitors by offering more than the mere ability to track orders and shipments, by aiming to improve all three groups of activities that make up a global trade—the order, the shipment, and the financial settlement.
6/18/2005

The Complex Handling of Complexity in Decision Support Systems » The TEC Blog
behavior; and managing big data volumes. Level of Complexity The Fact: Business processes are a not just a static set of steps to follow, rather they often change according to new constrains, or needs for improvement. As a consequence, almost every decision-making process has to deal with increasing levels of complexity derived from incremental modifications or functional adds to business models. Often, complexity increases because business processes tend to change, grow, and evolve, not the opposite.

DATA MODEL COMPLEXITY: complexity, Decision Support Systems, DSS, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
09-04-2010

Automation for the New Data Center
Data centers are squeezed by a variety of pressures, such as power consumption, heating, ventilating, and air conditioning (HVAC) requirements, new servers, human error, patching, asset tracking, and more. On top of this, you have to keep up with dynamically changing business requirements. One of the key ways you can address these dilemmas, however, is through server consolidation using virtualization.

DATA MODEL COMPLEXITY: Automation for the New Data Center Automation for the New Data Center Source: Novell Document Type: White Paper Description: Data centers are squeezed by a variety of pressures, such as power consumption, heating, ventilating, and air conditioning (HVAC) requirements, new servers, human error, patching, asset tracking, and more. On top of this, you have to keep up with dynamically changing business requirements. One of the key ways you can address these dilemmas, however, is through server consolidation
2/5/2007 9:40:00 AM

SAS Puts the “E” in “Data”
SAS Institute has applied its data mining technology to the Internet. The company released products that will help companies analyze and predict the behavior of Web surfers. The target customer is one with large volumes of enterprise data that come from a variety of sources.

DATA MODEL COMPLEXITY: provide analysis of the data collected at a website. Although the announcement covers three products, the SAS strategy is to present a solution that encompasses all of the data mining needs in a large enterprise. The WebHound product is a high-end clickstream analysis product. It analyzes the paths taken by customers viewing a website and can both produce standard traffic reports and answer ad hoc questions about the behavior of individuals or groups. E-Discovery is a data-mining product that can
3/27/2000

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.

DATA MODEL COMPLEXITY: The Dead-end of Dirty Data Why Systems Fail - The Dead-end of Dirty Data Olin Thompson - July 4, 2003 Read Comments Introduction 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. What is dirty data? When reality and the data in your system do not agree, you have dirty data. It may be as simple as having 1000
7/4/2003

Value-selling Maturity Model: Key to Sales in Tough Times
Showing value has always been key to greater sales and higher prices. However, the bar has been raised. It’s often no longer enough to claim value—now the customer has to see, believe, and care about the value. Sales organizations must get their eyes back on the value ball, with five value-selling maturity levels that tie in to sales effectiveness. Learn how to improve your revenues while reducing sales effort and costs.

DATA MODEL COMPLEXITY:
6/24/2009 11:30:00 AM

Overall Approach to Data Quality ROI
Organizations are beginning to wake up to the fact that the data they collect and manage should be viewed as a corporate asset. Data is the one thing that separates you from your competitors—and the quality of your data can be your competitive advantage or disadvantage. Discover six key steps you can take and put into effect to help you realize a tangible return on investment (ROI) on your data quality initiative.

DATA MODEL COMPLEXITY: Overall Approach to Data Quality ROI Overall Approach to Data Quality ROI Source: SAP Document Type: White Paper Description: Organizations are beginning to wake up to the fact that the data they collect and manage should be viewed as a corporate asset. Data is the one thing that separates you from your competitors—and the quality of your data can be your competitive advantage or disadvantage. Discover six key steps you can take and put into effect to help you realize a tangible return on investment
6/2/2009 4:06:00 PM

Virtualization Reduces Costs and Complexity for Midsized Businesses
Virtualization is a key element of the IT strategy for businesses of all sizes, with a variety of benefits for small and midsized businesses. It helps them to build an IT infrastructure with enterprise-class capabilities and it does so with a form factor—and a return on investment (ROI)—that fits any business. Discover how your business can use virtualization to reduce costs, improve services, and simplify management.

DATA MODEL COMPLEXITY:   blade servers,   datacenter server,   server clustering,   virtualize,   server infrastructure,   server provisioning Source: IBM Learn more about IBM Readers who downloaded this white paper also read these popular documents! Extending BI’s Reach: Anticipate Outcomes, Forecast Results, and Respond Proactively Sales Process Map Best Practices for ERP Implementation Best Practices for Fixed Asset Managers Talent Management for Small and Medium-size Businesses: Steer Your Business to Handle Change
6/2/2010 3:04:00 PM

Curing the Data Integration Migraine
The potential value of centralized data integration is enormous. Once implemented, integration systems promise to deliver more accurate and higher quality data. However, for those who venture into the world of implementation, the promise rarely matches the reality. Avoiding the “data integration migraine” requires careful planning to reduce the risks associated with data relationship, transformation, and map discovery.

DATA MODEL COMPLEXITY: Curing the Data Integration Migraine Curing the Data Integration Migraine Source: Exeros Document Type: White Paper Description: The potential value of centralized data integration is enormous. Once implemented, integration systems promise to deliver more accurate and higher quality data. However, for those who venture into the world of implementation, the promise rarely matches the reality. Avoiding the “data integration migraine” requires careful planning to reduce the risks associated with data
10/27/2006 4:30:00 PM


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