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Using Big Data Analytics to Better Understand Customers

Big data analytics has become so valuable to businesses of all sizes in all industries to help them analyze what customers really want.
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Maintaining a stand-alone, isolated data center is becoming outdated. The advantages of tapping cloud resources to expand computing power and data storage are just too attractive, especially as organizations mine more data resources such as the Internet of Things and implement big data projects. Software as a service (SaaS) and infrastructure as a service (IaaS) offer so many benefits that more companies are adopting a hybrid data center strategy that mingles on-site resources with public and private cloud computing. With hybrid data center design comes a new set of security challenges, and a new way to think about security.

Security and Hybrid Data Center Virtualization: What Every VAR Should Know

With hybrid data center design comes a new set of security challenges, and a new way to think about security.
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Is Big Data Solution Infrastructure to Blame for Security Breaches?

Big data solutions have to handle large quantities of data, so IT managers must be careful that data used for analytics do not create a security issue
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Data storage is becoming the biggest line item on the IT budget, especially with the boom in email traffic and the growing demand for data warehouses and big data. Data centers require access to more data storage, but it’s cost-prohibitive to maintain all that storage capacity in-house. That’s why more data center administrators are adopting hybrid data storage solutions.

Setting Up a Hybrid Storage Environment With Your Data Processing Center

Here are some considerations for data processing center administrators implementing a hybrid storage system.
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When you bring virtual resources into the data center, it can have a wide-ranging effect on the network infrastructure. Most of the impact will be on the physical plant and the enterprise capacity to accommodate the new virtual machines. There also are going to be power and cooling considerations, hardware configuration, and layout concerns that you will need to address before virtualization adversely impacts network performance.

The advantages of virtualization are clear. By encapsulating and abstracting applications from the physical hardware, you create virtual machines (VMs) that are easier to manage, are portable, and can be implemented on physical hardware in seconds. VMs make better use of shared data center resources and give IT managers complete control of server functions through a software overlay. More importantly, virtualization provides the elasticity needed to scale the infrastructure up or down, adding more VMs and cloud resources as needed to meet changing demands.

However, by virtualizing server technology, you now have a new set of architectural challenges, including server configuration and systems proliferation.

The Impact of Virtualization on a Data Center's Infrastructure

Virtualizing server technology presents new challenges, including server configuration and systems proliferation, to data center infrastructure.
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Adopting virtualization in the data center makes a lot of sense, especially if you are looking to optimize performance and reduce hardware costs. Virtualization offers a variety of benefits, particularly if you are hoping to increase resource availability and incorporate cloud capacity for applications such as big data. Of course, along with the benefits there are challenges as well.

One of the drivers of virtualization in the data center is the cost savings from using existing x86 server hardware for software upgrades.Infonetics Research also reports that 76 percent of the North American companies they surveyed see virtualization as an important driver for new security solutions. The survey also found that previously isolated virtual appliances are merging with software-defined networks (SDNs) to drive budgets up 57 percent in 2016. And research firmTechnavio predicts that the global virtualization market will jump from $10 billion in 2014 to $21.5 billion by 2019, largely because of increasing demand for cloud-based data systems.

So what are the advantages and obstacles of adopting virtualization in the data center?

The Six Big Challenges of Virtualizing a Data Center

Virtualizing a data center makes sense, especially if you are looking to optimize performance and reduce hardware costs, but there are also challenges
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As big data demands stretch established network infrastructures, IT architects have been adopting new strategies to expand the capabilities of enterprise networks. Big data requires rapid access to vast pools of data and the computing power to analyze that data, but conventional network design just doesn’t offer the bandwidth or the capacity. That’s why more big data infrastructures are increasingly relying on both server virtualization and software-defined networking (SDN). Although these two strategies have similarities, understanding the differences between them is important when designing an efficient big data infrastructure.

Understanding the Differences between SDN and Server Virtualization

When designing big data infrastructures , it's important to understand the differences between server virtualization and SDN.
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What is Network Functions Virtualization and Is it Better Than SDN?

In the context of big data, SDN and Network Functions Virtualization can work together to optimize data access and improve analytics performance.
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The one factor that often proves to be the biggest hurdle for big projects is data storage. Big data requires a great amount of data storage and, more importantly, storage versatility. Not only must the big data infrastructure have scalable storage that can accommodate massive quantities of data, but it also must deliver high-speed data access to meet the demands of big data analytics. Object data stores and software-defined storage (SDS) are gaining market momentum specifically because they address these big data storage headaches.

What Big Data Experts Need to Know About Software Defined Storage

Big data experts must guide customers toward adopting the right SDS strategies from the outset, eliminating barriers to data access.
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When value added resellers approach the task of implementing an integrated data storage project, chances are they’ll want to discuss with their customers the benefits and drawbacks of implementing either a converged or hyper-converged infrastructure.     

Integrated Data Storage: Converged Vs. Hyper-Converged Solutions

When VARs implement integrated data storage they should discuss benefits and drawbacks of implementing a converged or hyper-converged infrastructure
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As data center administrators look for technologies that simplify network functions while offering lower costs, greater scalability and improvements in network agility, two approaches are being embraced in the networking world: Software Defined Networking (SDN) and Network Functions Virtualization (NFV). While both offer new and different ways to design, implement and manage the network and its services, both have the capacity to significantly enhance network performance.    

5 Differences Between SDN and Network Functions Virtualization

Both Network Functions Virtualization (NFV) and SDN are growing in popularity, but how are the two different?
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