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Documents related to » analysis data


Data Management and Analysis
From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it

analysis data  Management and Analysis From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users Read More...
Role of In-memory Analytics in Big Data Analysis
Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be

analysis data  the data query and analysis process as well as ease data modeling by applying innovative ways for organizing and storing data. The table below lists some software products that use in-memory technologies for OLAP services.   Product Vendor PowerPivot Microsoft Cognos TM1 IBM Jedox OLAP Accelerator (GPU) Jedox WebFOCUS Visual Discovery Information Builders BIRT Data Objects and BIRT Data Analyzer Actuate Tableau Tableau Software Many products already incorporate in-memory technologies to provide fast Read More...
TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center
Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30

analysis data  Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the Read More...
How Bar Codes Can Optimize Data Recording and Information Analysis
Bar code technology allows users to analyze information to develop more accurate maintenance, personnel, and financial planning. In particular it can hasten the

analysis data  users to perform an analysis of the data records that will contribute to more accurate maintenance, personnel, and financial planning (maintenance budgets). About the author Juan Francisco Segura is an industrial engineer specializing in processes and automation. He has worked for the Universidad Iberoamericana, in Mexico City, as a computer technology consultant in the area of physics, arranging electronic and computing equipment for their labs. During the last six years, he has worked as a computer Read More...
Business Analytics: Benchmarking the Analysis of Data to Gain Insight
Organizations are maturing only slowly in their use of analytics despite the fact that they view them as valuable and important. This research indicates that

analysis data  Analytics: Benchmarking the Analysis of Data to Gain Insight Organizations are maturing only slowly in their use of analytics despite the fact that they view them as valuable and important. This research indicates that usability and flexible functionality are important criteria in their search for the right analytics; that failing to examine timely availability, broad access, and efficient handling can obstruct analytics use; and that in technology terms, spreadsheets should be replaced with more Read More...
Types of Prefabricated Modular Data Centers
Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod

analysis data  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More...
Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise
While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to

analysis data  Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help. 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

analysis data  Integration , Data Quality Analysis , Data Quality Approach , Data Quality Assessment , Data Quality Best Practices , Data Quality Campaign , Data Quality Control , Data Quality Framework , Data Quality Improvement , Data Quality Indicator , Data Quality Indicators , Data Quality Issue , Data Quality Issues , Data Quality Management , Data Quality Management Model , Data Quality Management Tools , Data Quality Measurement , Data Quality Measures , Data Quality Method , Data Quality Metrics , Data Quality Read More...
Six Steps to Manage Data Quality with SQL Server Integration Services
Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business

analysis data  Improvement , Data Quality Analysis , Data Quality Articles , Data Quality Assessment , Data Quality Indicator , Data Quality Indicators , Data Quality Business Intelligence , Data Quality Initiatives , Data Quality Issues , Data Quality Management , Data Quality Measurement , Data Quality Measures , Data Quality Methodology , Data Quality Methods , Data Quality Metrics , Data Quality Model , Data Quality Objectives , Data Quality Plan , Data Quality Problems , Data Quality Process , Data Quality Read More...
2012 Business Data Loss Survey results
This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download

analysis data  Business Data Loss Survey results This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now. 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

analysis 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 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...
Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations
While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as

analysis data  Data Analytics: Profiling the Use of Analytical Platforms in User Organizations While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of big data and the use of analytics to mine that data. Read More...
Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics
Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident

analysis data  Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk Read More...

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