A high percentage of today’s data centers use water-based cooling methods. Although evaporative cooling, whether through traditional towers or “advanced” adiabatic cooling systems (aka swamp coolers), remain highly effective cooling methods, when you’re planning a new data center you may want to consider the impact of the weather and water availability on your decision.
Cisco's Virtualized Multi-tenant Data Center (VMDC) system defines an end-to-end architecture, which an organization may reference for the migration or build out of virtualized, multi-tenant data centers for new cloud-based service models such as Infrastructure as a Service (IaaS).
Cisco has developed robust infrastructure management tools for your Cisco Unified Computing System™ (Cisco UCS™) data center that work with and extend tools you may already use to monitor, provision, configure, and orchestrate your Microsoft server and application software.
Cisco ne cesse d'innover afin d'aider les sociétés à réinventer le data center d'entreprise et à délivrer d'excellentes prestations pour un plus grand impact commercial. Dans cet objectif, Cisco a développé de solides outils de gestion de l'infrastructure pour votre data center Cisco Unified Computing System™ (Cisco UCS™). Ces outils se combinent et étendent l'utilité de ceux que vous avez pour surveiller, provisionner, configurer et orchestrer vos logiciels serveur et d'application Microsoft.
Published By: Teradata
Published Date: Mar 10, 2014
We evaluate vendors providing applications that support the management of marketing resources, such as plans, people, budgets, projects, tasks, assets and cycle times. This Magic Quadrant will help marketing leaders and CIOs find an MRM solution to better manage their marketing resources.
Understanding the data you have and put it to effective use is now more crucial than ever. The key differentiator between the leaders and laggards in financial services today is how skillfully they turn data into useful information and fuel success.
Armed with their opinions and social media accounts, your customers have the kind of clout to influence your brand that last century’s ad men only dreamed about. Learn how your organization can securely capture, analyze, and act upon 100 percent of the data available to you.
Today's data landscape brings enormous opportunity to organizations to derive insights from all their data. Learn how government departments, agencies, public healthcare providers, and educational institutions can harness the value of Big Data today.
Big Data is an opportunity for CSPs to create the intelligence for operating networks more efficiently, to analyze the success of the services that telcos are offering, and to create a better personal experience for their customers. Learn how to leverage the Big Data opportunity.
There are many new ways Big Data analytics can significantly boost marketing and promotional efforts through real-time and historical analysis of online data, such as clickstream or purchase transactions. Unstructured data based on social media—even photos and video—offers enormous potential when analyzed with the right tools.
"Improving the operational aspects of a business can span the organizational chart, from line of business teams focused on the supply chain to IT teams reporting on communication networks and their switches. The goal is to capture the data streaming in from these various processes, and put Big Data techniques to work for you."
Security breaches can happen anywhere in an organization, and having the ability to analyze any form of data can give you the edge against fraud, theft, and infiltration by pinpointing abnormal behavior patterns. Understanding your security vulnerabilities requires rapid, deep analytics against business data, machine data, and unstructured human information.
HP HAVEn is the industry’s first comprehensive, scalable, open, and secure platform for Big Data. Enterprises are drowning in a sea of data and need a trusted partner to help them. HP HAVEn has two primary components: a platform and an ecosystem. Together, the platform and the ecosystem provide the capability to handle 100 percent of your enterprise data—structured, unstructured, and semi-structured—and securely derive actionable intelligence from that data in real-time.
We’ve heard it before. A data warehouse is a place for formally-structured, highly-curated data, accommodating recurring business analyses, whereas data lakes are places for “raw” data, serving analytic workloads, experimental in nature. Since both conventional and experimental analysis is important in this data-driven era, we’re left with separate repositories, siloed data, and bifurcated skill sets.
Or are we? In fact, less structured data can go into your warehouse, and since today’s data warehouses can leverage the same distributed file systems and cloud storage layers that host data lakes, the warehouse/lake distinction’s very premise is rapidly diminishing. In reality, business drivers and business outcomes demand that we abandon the false dichotomy and unify our data, our governance, our analysis, and our technology teams.
Want to get this right? Then join us for a free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guest, Dav
Published By: Dell EMC
Published Date: Mar 18, 2016
This report documents hands-on testing and validation of an EMC data protection solution for virtual environments using Avamar Virtual Edition with a Data Domain system, with a focus on the ease of integration, efficiency, scalability, and backup/restore performance.
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it’s readily available to be categorized, processed, analyzed, and consumed by diverse groups within an organization. Since data - structured and unstructured - can be stored as-is, there’s no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
Published By: LogRhythm
Published Date: Aug 08, 2016
THE TIME HAS come for CEOs and Boards to take personal responsibility for improving their companies’ cyber security. Global payment systems, private customer data, critical control systems, and core intellectual property are all at risk today. As cyber criminals step up their game, government regulators get more involved, litigators and courts wade in deeper, and the public learns more about cyber risks, corporate leaders will have to step up accordingly.
Mobile device management (MDM) tools allow companies to connect their employees securely to basic corporate network resources. Enterprise mobility management (EMM) goes a step further by enabling secure mobile versions of business-critical applications and data loss prevention to protect corporate information. But in today's workplace, employees and businesses deal with a vast variety of devices with different operating systems and form factors, from PCs and laptops, to tablets and smartphones, and now, increasingly wearables and Internet of Things (IoT) endpoints. The solution is unified endpoint management (UEM), which enables organizations to take a consistent approach to manage and secure every endpoint, any app and content, and across deployment use cases from a single holistic platform. Read this whitepaper to uncover VMware AirWatch®'s leading UEM approach that is benefiting organizations tremendously.
Published By: Datastax
Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
Published By: Datastax
Published Date: Apr 04, 2017
Enterprises today continue to differentiate themselves with cloud applications – any application that needs to be always-on, distributed, scalable, real-time, and contextual. With DataStax Enterprise, DataStax delivers comprehensive data management with a unique always-on architecture that accelerates the ability of enterprises, government agencies, and systems integrators to power the exploding number of cloud applications. DataStax Enterprise (DSE) powers these cloud applications that require data distribution across data centers and clouds, by using a secure, operationally simple platform. At its core, DSE offers the industry’s best distribution of Apache Cassandra™.
This paper provides a summary of the features and functionality of DataStax Enterprise that make it the best choice for companies that are looking to leverage the promise of Apache Cassandra™ for production environments.
Published By: Datastax
Published Date: Apr 04, 2017
Graph databases are changing how we use data. But first, an example – you're (probably) a human working on a project and looking at graph databases as a potential solution. While we're a company that has a graph database that hopefully solves your problem. Now we could store that data in a boring relational database, but how do we do more than that? For instance, using that data, when combined with other data points, to find other people like you and recommend our solution to them? This is where a graph can come in handy.
The friendly graph data model makes it easy to use patterns of relationships within large data sets. By leveraging those relationships we can analyze, or create better real-time experiences. Why Graph explores why this graph database 'thing' is really a thing, how they compare to other database systems, and the use cases they best support.
Como evitar a escolha do dispositivo errado para sua aplicação. Para uma visão mais completa de cada consideração, faça download do nosso documento técnico. Ele destaca razões para escolher os dispositivos de nível empresarial em vez de dispositivos de consumo, incluindo:
• As principais considerações sobre desempenho de digitalização
• A importância do gerenciamento de energia e dos acessórios certos
• A importância da conectividade e porque nem todos os dispositivos são feitos da mesma maneira