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Data Leak versus Data Flood: Problems Addressed by Data Leakage and Data Breach Solutions
Data leakage and data breach are two disparate problems requiring different solutions. Data leakage prevention (DLP) monitors and prevents content from leaving
by Data Leakage and Data Breach Solutions Data leakage and data breach are two disparate problems requiring different solutions. Data leakage prevention (DLP) monitors and prevents content from leaving a company via e-mail or Web applications. Database activity monitoring (DAM) is a data center technology that monitors how stored data is accessed. Learn why DAM complements DPL, and how you can benefit by making it part of your overall data security strategy.
Core PLM--Product Data Management - Discrete RFI/RFP Template
Product Data Management (PDM), Engineering Change Order and Technology Transfer, Design Collaboration, Process and Project Management, Product Technology
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Outsourcing, IT Infrastructure
The IT Infrastructure Outsourcing knowledge base focuses on the selection of companies who provide outsource services in the areas of information technology (IT) infrastructure. The typical type...
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Security Breach: Now What?
When people's lives or financial transactions are at risk, proper Security Incident handling is of extreme importance.
or proprietary data. System data (root directories) and log files. User, application, and program data. Mitigation of disruption to Information Resources If one of the Incident Goals is to pursue and prosecute, note that it is very important not to tamper with the evidence. This means that log files cannot be edited, and access and creation dates and times cannot be changed on any files, applications, or data resources. If data is overwritten, transferred to another system, or sent across unencrypted
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
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.
The Path to Healthy Data Governance through Data Security
Companies today are challenged to maintain their data safe and secure from hackers and others with unauthorized access. In his article, TEC business
Path to Healthy Data Governance through Data Security The appropriate handling of an organization’s data is critically dependent on a number of factors, including data quality, which I covered in one of my earlier posts this year. Another important aspect of data governance regards the managing of data from a security perspective. Now more than ever, securing information is crucial for any organization. This article is devoted to providing insight and outlining the steps that will put you on the path
Managing Encryption Keys: Best Practices for Ensuring Data Recoverability
Heightened awareness of vulnerabilities in sensitive stored data has resulted in the increased application of encryption technology. To secure data at rest, a
validates that the recovery data has not been tampered or otherwise corrupted while in storage. Key handling In order to prevent exposure and breach of secured data, CipherMax has been designed to employ secure techniques for handing keys both internal and external to the device. These measures include: Encryption keys never leave the CipherMax system chassis in cleartext form. The encryption key database is secured with the Master Key in AES-256 format before keys can be exported to KeyCruiser. Data
Unified Data Management: A Collaboration of Data Disciplines and Business Strategies
In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration
Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts.
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
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
Data Warehousing in the Big Data Era: Are You BIReady?
Netherlands-based BIReady automates the process of designing, deploying, and maintaining a data warehousing solution, allowing the optimization of all necessary
Warehousing in the Big Data Era: Are You BIReady? Netherlands-based BIReady automates the process of designing, deploying, and maintaining a data warehousing solution, allowing the optimization of all necessary BI and analytics tasks. Read this TEC product note from TEC senior BI and data management analyst Jorge Garcia to learn more about how BIReady is meeting its goal of helping companies become BI ready.
Developing a Universal Approach to Cleansing Customer and Product Data
Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data
Cleansing Customer and Product Data Developing a Universal Approach to Cleansing Customer and Product Data 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 Frankfurt Stock Exchange and NYSE under the symbol SAP.
Big Data, Little Data, and Everything in Between—IBM SPSS Solutions Help You Bring Analytics to Everyone
Regardless of the type or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the
or scale of business data your users need to harness and analyze, they need a straightforward, visual solution that is easy to use on the front end and highly scalable on the back end. Fortunately, IBM SPSS solutions provide just such an ecosystem that can make different kinds of data stores—from Hadoop to those proverbial spreadsheets—useful sources of business insight and decision support.
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete
aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are
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
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.
Data Center Projects: Project Management
In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined
leading causes of downtime, data loss and hardware damage: power problems and temperature. As a global leader in network-critical physical infrastructure (NCPI) solutions, APC sets the standard in its industry for quality, innovation and support. Source : APC Resources Related to Data Center Project Management : Data Center (Wikipedia) Project Management (Wikipedia) Data Center Projects: Project Management Data Center Project is also known as : Project Management , Internalize Data Centers , Data Center
Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a
Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization's customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case.
Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company
Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.
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