What does Big Data mean to traditional enterprise IT? Organizations of any size and industry are becoming more and more aware of the incredible importance of capturing, managing and analyzing the data available to them. The more comprehensively companies are able to tap structured and unstructured data sources, the quicker they can refresh this data and the more successfully they make this body of data available to all business units, the better they can develop advantages in the market place. Today’s business units are demanding the rapid implementation of these big data use cases, as well as optimal resiliency, cost efficiency, security and performance.

We are about to launch an EMA research project that will analyze the implications of big data analytics for systems management from the perspective of IT operations staff. Servers, networks, storage and the automation and management solutions that keep them running efficiently need to dramatically adjust to these new requirements.

The following questions will be answered:

What are the key infrastructure obstacles –internal and external– of big data deployments?

What are the perceived data center and cloud-related key pain points of big data deployment projects?

How to best integrate big data architectures with traditional data center and cloud infrastructure?

How to ensure end-to-end visibility across the big data capture, management and analysis process?

How to ensure performance, scalability, elasticity and manageability of enterprise big data environments?

How can big data co-exist with traditional application environments?

How can customers best take advantage of physical, virtual and cloud infrastructure for big data?

What are the roles of automation and analytics when creating and managing big data infrastructure?

What is the impact of Big Data on traditional IT roles, processes and data center silos?

How to ensure performance, security and SLA compliance of big data infrastructure?

Which key technologies and architectures are required to better benefit from big data projects?

What governance, automation and orchestration platforms are needed for optimal infrastructure management?

How can Big Data projects take optimal advantage of private and public cloud?

How does Big Data analytics help support enterprise IT management?

The result of this end-user research will be a clear cut set of check lists for IT professionals to determine how IT operations should adjust to big data requirements in the short and long term.Vendors will have the opportunity to determine how their offerings align with customer requirements in the big data context.

Needless to say that I’m very much looking forward to getting started.

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