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Meeting the Challenges of Product Traceability with Automated Data Collection
An effective traceability system involves determining which product and manufacturing process attributes to collect and maintain@and deciding when during the

data collection forms  Product Traceability with Automated Data Collection The backbone of Radley's WorkForce Productivity Solutions is x/DC, a .Net, XML based data collection development and integration platform. x/DC’s client/server architecture offers scalability, performance and availability unachievable by other solutions. Source : Radley Corporation Resources Related to Meeting the Challenges of Product Traceability with Automated Data Collection : Traceability (Wikipedia) Data Collection (Wikipedia) Meeting the Read More...
Enterprise Content Management (ECM)
A content management system is a software package designed to manage an organization''s entire collection of documents, records, and other information assets. Content mana...
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Documents related to » data collection forms


3 Big Trends in Data Visualization
The greatest value of a picture is when it forces usto notice what we never expected to see.—John W. Tukey. Exploratory Data Analysis. 1977.Data

data collection forms  Big Trends in Data Visualization The greatest value of a picture is when it forces us to notice what we never expected to see. —John W. Tukey. Exploratory Data Analysis . 1977. Data visualization is core to business intelligence (BI), as it’s the means by which data is communicated to the user. Results, alerts suggestions, or even more controlled guidance—all of these elements are passed through the data visualization function of a BI application. No matter how much importance software providers giv Read More...
A CRM System Needs A Data Strategy
A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact

data collection forms  acquisition and retention efforts, data collection cannot be an end unto itself. In fact, a data strategy is needed to target and keep the right types of customers. For vendors and IT managers to help enterprise users, this is an overview of how they can develop and implement a data strategy to guide both the acquisition and retention phases of a marketing campaign - within which a CRM system can be optimally flexed. Supporting Acquisition The first goal in the acquisition phase must be deciding which pro Read More...
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

data collection forms  Data Warehouse: The term Data Warehouse was coined by Bill Inmon in 1990, which he defined in the following way: A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process . He defined the terms in the sentence as follows: Subject Oriented: Data that gives information about a particular subject instead of about a company's ongoing operations. Integrated: Data that is gathered into the data warehouse from a variety of Read More...
Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

data collection forms  BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of their data as well as to ways to capture the most valuable information for improved decision making and business performance. Let’s look at what the data tells us. Below is a Pareto chart based on data from Technology Evaluation Centers (TEC) on what software users consider to be the most popular functionality features for BI applicati Read More...
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

data collection forms  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 Unisphere 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 Read More...
An Improved Architecture for High-efficiency, High-density Data Centers
Globally, data center power and cooling infrastructure wastes more than 60 million megawatt-hours per year that do not contribute usefully to powering IT

data collection forms  Architecture for High-efficiency, High-density Data Centers An Improved Architecture for High-Efficiency, High-Density Data Centers If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. In today's always on, always available world where businesses can't stop and downtime is measured in dollars, American Power Conversion (APC) provides protection against some of the leading causes of downtime, data loss and hardware damage: power problems 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 collection forms  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...
Fundamentals of Managing the Data Center Life Cycle for Owners
Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and

data collection forms  of Managing the Data Center Life Cycle for Owners Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and o Read More...
Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

data collection forms  Masking: Strengthening Data Privacy and Security Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you. Read More...
Master Data Management: Extracting Value from Your Most Important Intangible Asset
In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe

data collection forms  Data Management: Extracting Value from Your Most Important Intangible Asset Master Data Management: Extracting Value from Your Most Important Intangible Asset If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Founded in 1972, SAP has a rich history of innovation and growth as a true industry leader. SAP currently has sales and development locations in more than 50 countries worldwide and is listed on several exchanges, including the Read More...
Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

data collection forms  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration Read More...
Protecting Critical Data
The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data

data collection forms  Critical Data The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly. Read More...
Flexible Customer Data Integration Solution Adapts to Your Business Needs
Siperian's master data management and customer data integration (CDI) solutions allow organizations to consolidate, manage, and customize customer-related data.

data collection forms  Customer Data Integration Solution Adapts to Your Business Needs Customer data integration (CDI) has become one of the buzzwords within the master data management (MDM) industry. Although the concept of creating a single organizational view of the customer is noble and desirable, its value should also be justified by organizations. To implement a customer data hub that only creates a centralized view of an organization's customer-related data does not affect a company's bottom line, unless Read More...

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