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Siemens’ Active Workspace Handles PLM Data Complexity
Today, many companies have massive amounts of information generated from their product lifecycle processes currently lying dormant, often spread across many

data model complexity  uses Siemens PLM’s Teamcenter data model and customer’s existing style sheets to adapt to industry and customer preferences. Figure 3 shows Active Workspace’s Web-based filtering and intelligent charts, making it easy for users to find what they need without having to know/understand the underlying PLM data model. Figure 3 – Search with Intelligent Charts and Filters In addition to an HP Autonomy plus Solr -based search engine, Active Workspace has a 3D-shape geometry Geolus search engine that Read More...
Discrete Manufacturing (ERP)
The simplified definition of enterprise resource planning (ERP) software is a set of applications that automate finance and human resources departments and help manufacturers handle jobs such as or...
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Documents related to » data model complexity


Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio
Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the

data model complexity  do you foresee? Cloud-based data warehousing is emerging as a deployment model for large-scale analytics and Kognitio has always offered this—helping businesses to solve several issues that are commonplace today. Most notably, the inability to prove business value from data warehousing and analytics projects before spending large capital sums of money. By running analytics in the cloud, there is no overhead of implementing a data warehouse onsite, and there is no need for an information technology (IT) Read More...
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

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, Read More...
Is the SaaS Model Right for You?
For IT departments drowning in complex and expensive software maintenance chores, the software-as-a-service (SaaS) model can ease the burden. SaaS reduces

data model complexity  strategic value/risk associated with data stored or processed in the cloud? How vulnerable is your own organization to security threats relative to cloud providers? Disaster Recovery: Can the cloud provider meet the RTO/RPO requirements associated with this project/ application/data? Performance: What is the cloud provider's SLA commitment and track record in meeting that commitment? Are there resources available for performance monitoring? What impact will latency have on performance? Architecture & Read More...
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

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. Read More...
A Roadmap to Data Migration Success
Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources,

data model complexity  Roadmap to Data Migration Success Many large business initiatives and information technology (IT) projects depend upon the successful migration of data—from a legacy source, or multiple sources, to a new target database. Effective planning and scoping can help you address the associated challenges and minimize risk for errors. This paper provides insights into what issues are unique to data migration projects and to offer advice on how to best approach them. Read More...
A Solution to Data Capture and Data Processing Challenges
Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the

data model complexity  Solution to Data Capture and Data Processing Challenges Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems. 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 model complexity  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...
Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management
Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in

data model complexity  the Supply Chain-Focusing on Data Quality and Master Data Management Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset. Read More...
How to Use Data Management Successfully
Find out in the white paper master data management: extracting value from your most important intangible asset.

data model complexity  to Use Data Management Successfully Did you know that effective master data management (MDM) is a critical component in an efficient, successful business? With the amount of data in a typical organization escalating dramatically, data management has become your most important intangible asset . If you aren't managing your master data effectively, you could be opening the door to a host of problems: Part of your company is doing business with a client or account, but other parts of the company aren't Read More...
Considerations for Owning versus Outsourcing Data Center Physical Infrastructure
When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both

data model complexity  for Owning versus Outsourcing Data Center Physical Infrastructure When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life Read More...
Data Quality: Cost or Profit?
Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and

data model complexity  number of articles about data quality. ( Poor Data Quality Means A Waste of Money ; The Hidden Role of Data Quality in E-Commerce Success ; and, Continuous Data Quality Management: The Cornerstone of Zero-Latency Business Analytics .) This time our focus takes us to the specific domain of data quality within the customer relationship management (CRM) arena and how applications such as Interaction from Interface Software can help reduce the negative impact that poor data quality has on a CRM objective. Read More...
Tailoring SAP Data Management for Companies of All Sizes
The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are

data model complexity  SAP Data Management for Companies of All Sizes The need for accurate data management such as upload or download of data between a company’s data sources and SAP systems is more critical than ever. Users are relying on manual operations, which are inherently error-prone, and time- and resource-intensive. Today's environment requires enterprise-class automation to overcome these challenges of data management. Learn about one solution that can help improve SAP data management. Read More...

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