Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Read this MIT Technology Review custom paper to learn how advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics, helping to accelerate business outcomes for data driven organizations.
The data residing on your storage systems and media, data-at-rest, presents serious security concerns. Regulations and various mandates around the world are putting the burden on companies and government entities to protect the private information they store. Increasingly, companies are being required to publicly disclose breaches that put individuals private data at risk, be it a customer, employee, shareholder, partner, or other stakeholder.
F5 and Data Domain have joined their respective solutions, forming a partnership designed to assist customers in deploying and realizing the benefits of tiered storage. By combining F5’s tiered storage policy engine with Data Domain deduplication storage systems, mutual customers can realize the benefits of deploying tiered storage and, importantly, see dramatic reductions in the costs of storage.
Frustrated by the costs of maintain ever larger data centers-or building new ones-many companies are exploring virtualization. Virtualization lets your IT staff turn your data center into an internal cloud of computing resources controlled by a single virtual data center operating system (VDC-OS).
Today's use of virtualization technology allows IT professionals to automatically manage the resources of the physical server to efficiently support multiple operating systems, each supporting different applications. This IDC Technology Assessment presents IDC's view of how virtualization technologies are impacting and will continue to impact operating environments and the operating environment market near- and long-term.
VMware virtualization enables customers to reduce their server TCO and quickly delivers signification ROI. This paper describes commonly used TCO models and looks at several case studies that apply TCO models to virtualization projects. Learn more.
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.
"As the rapid rise in the number of mobile devices and users creates an explosion in data and virtual machine instances, datacenter transformation becomes imperative for many enterprises. It is essential enterprises move to consolidate resources and cut both capital and operating costs while still providing support for distributed applications.
This brief white paper delves into a Q&A with Eric Sheppard, research director of IDC’s Storage Software program, on integrated systems and whether you should buy compute, network, and storage resources together. Read on as you will discover:
What integrated systems are, and its benefits
The differences between an integrated platform and integrated infrastructure
How datacenters are leveraging these new systems today
This is a white paper that assumes familiarity with Oracle database administration as well as basic Linux system and storage administration tasks as required for a typical database installation, such as creating partitions and file systems. The Pure Storage Flash Array is ready to run your Oracle database with no changes to your existing configuration. You can realize significant improvements in performance and ease of manageability
94% of IT professionals consider it valuable to manage data based upon the business value of it. Yet only 32% are doing it - because it's hard. Are you looking to be a part of the 32% without the difficulties?
There is a substantial gap between those who want to use data to its full potential and those that are actually doing so. Storage systems have never been designed with the end-goal to help customers prioritize their data based on their own priorities and the value of that data.
Narrowing that gap may not be as hard or expensive as many companies think. Solving these challenges was one of the founding principles around NexGen's Hybrid Flash Array.
Download now and learn how IT professionals can use NexGen storage architecture and software to simplify data priority assignment and management process.
This white paper details how continuous data protection for files is important in this current day where lost data can significantly affect productivity, customer satisfaction, and, ultimately, revenue.
As it has been the trend over the last decade, organizations must continue to deal with growing data storage requirements with the same or less resources. The growing adoption of storage-as-a-service, business intelligence, and big data results in ever more Service Level Agreements that are difficult to fulfill without IT administrators spending ever longer hours in the data center. Many organizations now expect their capital expense growth for storage to be unstoppable, and see operating expense levers - such as purchasing storage systems that are easy to manage - as the only way to control data storage-related costs.
As data volumes grow, you need more than just storage space. Let us help you orchestrate a solution that brings you the scalability and agility you need to move your organization forward.
Storage needs are changing rapidly, and legacy appliances and processes just can’t keep up. Old systems are running slowly and filling up fast. At CDW, we can help you evolve your storage with a smart solution that’s ready for what lies ahead.
Years of IT infrastructure advancements have helped to drive out vast amounts of costs within the datacenter. Technologies like server and storage virtualization, data deduplication, and flash-based storage systems (to name just a few) have contributed to improvements of utilization rates, performance, and resiliency for most organizations. Unfortunately, organizations still struggle with deeply rooted operational inefficiencies related to IT departments with silos of technology and expertise that lead to higher complexity, limited scalability, and suboptimal levels of agility. The recent tectonic shifts caused by the rise of 3rd Platform applications that focus on social, mobile, cloud, and big data environments have amplified the pains associated with these structural inefficiencies.
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic 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 enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? 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.
With flash based systems now commonly in the TBs of capacity and rapidly becoming more affordable, it may be time to look at using solid state storage with high bandwidth applications. Read this white paper to find out more.
Most companies have only put limited effort toward the system architecture that surrounds the flash memory modules. In this white paper, Storage Switzerland focuses on the importance of architecture design in solid state storage systems.
In this part II of Enhancing Server And Desktop Virtualization With SSD, Storage Switzerland focuses on the next challenge of integrating SSD into a virtual server or desktop infrastructure and effectively using the technology in this environment.
In this final piece on server virtualization and SSD, Storage Switzerland discusses the power of performance, specifically, the dramatic impact that latent-free storage can make on the virtual environment. Read on to find out more!
A huge array of BI, analytics, data prep and machine learning platforms exist in the market, and each of those may have a variety of connectors to different databases, file systems and applications, both on-premises and in the cloud. But in today’s world of myriad data sources, simple connectivity is just table stakes.
What’s essential is a data access strategy that accounts for the variety of data sources out there, including relational and NoSQL databases, file formats across storage systems — even enterprise SaaS applications — and can make them all consumable by tools and applications built for tabular data. In today’s data-driven business environment, fitting omni-structured data and disparate applications into a consistent data API makes comprehensive integration, and insights, achievable.
Want to learn more and map out your data access strategy? Join us for this free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guests, Eric
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated
drive as you read the morning news. We are getting very close to that kind of
scenario, and companies like Ford expect to have production vehicles in the latter part
Driverless cars are just one popular example of machine learning. It’s also used in
countless applications such as predicting fraud, identifying terrorists, recommending
the right products to customers at the right time, and correctly identifying medical
symptoms to prescribe appropriate treatments.
The concept of machine learning has been around for decades. What’s new is that
it can now be applied to huge quantities of data. Cheaper data storage, distributed
processing, more powerful computers and new analytical opportunities have dramatically
increased interest in machine learning systems. Other reasons for the increased
momentum include: maturing capabilities with methods and algorithms refactored to
run in memory; the
This report covers the challenges of first generation deduplication technology and the advantages of next-gen deduplication products. Next generation Dedupe 2.0 systems use a common deduplication algorithm across all storage systems-whether they're smaller systems in branch offices or large data center storage facilities. That means no more reconstituting data as it traverses different storage systems, which saves bandwidth and improves performance.