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Abstract: 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.
PubDate: 3/19/2008 6:10:00 PM
Abstract: Being number two in the advanced planning and scheduling (APS) software market is becoming a coveted prize for old guard ERP vendors.
Abstract: Una vez atravesados los problemas del ERP en los noventa, en el año 2000 logra alcanzar su madurez, enfrentándose al mismo tiempo con problemas tales como la regionalización y la actualización de versiones, entre otros. Actualmente se acerca otra etapa en la resolución del modo administrativo, en la que el problema del ERP será atacado con productos de plataforma.
Abstract: ERP se puede definir como una aplicación de gestión empresarial diseñada para cubrir las áreas funcionales de la empresa. Es un paquete de aplicaciones que integra a cada una de las áreas de la empresa creando un flujo de trabajo entre los distintos usuarios. Este flujo permite evitar tareas repetitivas y aumentar la comunicación entre las áreas a través de la disposición de información en tiempo real.
Abstract: A partir de éste artículo analizaremos la problemática del mercado ERP a fines de los noventa y paralelamente el gran surgimiento del CRM, lo cual nos lleva a reflexionar sobre el rol de cada uno y los límites de la integración. Ante esta situación, podemos encontrar otra manera de encarar el problema, que es a través de la generación de un marco de trabajo de objetos de negocios en el cual al momento de definir los objetos la diferencia ERP-CRM queda casi nula y para lo cual Calipso ha creado Biframe.
Abstract: 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.
Abstract: Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.
Abstract: 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.
Abstract: 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.
Abstract: Companies are fighting a constant battle to integrate business data and content while managing data quality. Data quality serves as the foundation for business intelligence (BI), enterprise resource planning (ERP), and customer relationship management (CRM) projects. Learn more about software that unifies leading data quality and integration solutions—helping your organization to move, transform, and improve its data.
Abstract: 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.
Abstract: 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.
Abstract: 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 it is crucial to getting maximum value out of your data. In small companies, for which every sales lead, order, or potential customer is valuable, poor data quality isn’t an option—implementing a thorough data quality solution is key to your success. Find out how.
Abstract: As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.
Abstract: 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.
Abstract: Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.
Abstract: Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.
Abstract: Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more.
Abstract: If you can’t see how your business is performing, how can you make the right decisions? For a company to thrive, operations and analysis must work together. The ability to access and integrate all your data sources is the start to getting the complete picture—and the key to not compromising your decision-making process. Learn more about how data integration can help consolidate your data so you can use it effectively.