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The Why of Data Collection
Data collection systems work; however, they require a investment in technology. Before the investment can be justified, we need to understand why a data

data collection methods  Why of Data Collection Introduction Data collection systems work. However, they mean an investment in technology. Before we can justify that investment, we need to understand why we may want to use a data collection system in place of people with clipboards. What is data collection? In a general sense, it is the manual or automated acquisition of data. That definition has evolved to mean various automated methods of data acquisition. Examples of data collection include time and attendance devices, bar 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 methods


Understanding the PCI Data Security Standard
The payment card industry data security standard (PCI DSS) defines a comprehensive set of requirements to enhance and enforce payment account data security in a

data collection methods  network resources and cardholder data be tracked, and must be logged for subsequent auditing and review. A wide variety of tools and techniques are employed to conduct such testing. The well-known and well-documented security discipline known as penetration testing comes into play, as highly trained outside consultants or testing organizations probe and seek to break through perimeter, software and physical defenses. This effort involves testing humans to ensure they: Comply with security guidelines Read More...
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 methods  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...
Deploying High-density Zones in a Low-density Data Center
New power and cooling technology allows for a simple and rapid deployment of self-contained high-density zones within an existing or new low-density data center

data collection methods  sized zones or smaller data centers (less than 20 racks) with no previous experience. A worksheet and checklist is provided in Appendix A. This worksheet can serve as a helpful guide and facilitates the collection of information required to specify and deploy a high-density zone. The worksheet assumes the project owner has knowledge of the IT equipment associated with the planned high-density zone (e.g. total power requirements, plug requirements, rack U-height requirements, and communications cabling Read More...
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

data collection methods  quality and usability of data that is captured via collection methods that support the principles of responsible asset stewardship. It can also be seen that advances in modern technology, combined with the growing needs of asset intensive companies, have enabled this information to be used in newer and more comprehensive ways than originally conceived of, and correspondingly, this information is not mentioned in previous work on RCM. In particular, it fuels the shift by the company away from static Read More...
Next-generation Data Auditing for Data Breach Protection and Risk Mitigation
Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation

data collection methods  generation Data Auditing for Data Breach Protection and Risk Mitigation Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system. 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 methods  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 methods  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...
The Advantages of Row- and Rack-oriented Cooling Architectures for Data Centers
The traditional room-oriented approach to data center cooling has limitations in next-generation data centers. Next-generation data centers must adapt to

data collection methods  Rack-oriented Cooling Architectures for Data Centers The Advantages of Row and Rack-Oriented Cooling Architectures for 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...
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 methods  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 Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution
There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting

data collection methods  Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting firms across the globe willing to help you build them. However, it’s imperative for each data management solution to specialize to the unique needs of your organization’s business users, across varying functional areas. Read More...
Operationalizing the Buzz: Big Data 2013
The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the

data collection methods  the Buzz: Big Data 2013 The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use Read More...
Optimizing Gross Margin over Continously Cleansed Data
Imperfect product data can erode your gross margin, frustrate both your customers and your employees, and slow new sales opportunities. The proven safeguards

data collection methods  Margin over Continously Cleansed Data Optimizing Gross Margin over Continously Cleansed Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Advanced functionality to manage costs, sell prices, promotions, discounts, chargebacks, and other key attributes while optimizing gross profits. Source : epaCUBE Resources Related to Optimizing Gross Margin over Continously Cleansed Data : Data cleansing (Wikipedia) Gross margin (Wikipedia) Read More...
Appliance Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever
Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online

data collection methods  Power: Crunching Data Warehousing Workloads Faster and Cheaper than Ever Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility. Read More...
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but

data collection methods  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Read More...

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