There’s no doubt that big data offers big benefits to the enterprise. Improved productivity, better insight into customer experience, and process optimization are just a few ways that teams can get ahead with the technology. In fact, the number of companies implementing big data projects has grown exponentially.
According to a study by IDG, nearly half of 751 respondents said they are in the process of implementing, or likely to implement a big data project in the near future. The top ten percent have already done it.
But for the individuals who have undertaken such an endeavor, what have been the real-world impacts? How does it affect the network? More importantly, how has it changed how network and applications teams deliver great service, and what are the top concerns?
“With big data projects, there’s a lot of information coming in, and it has to be in real time in order to be effective and precise,” says Jim Rapoza, Senior Research Analyst of Network and Application Performance at Aberdeen Group. “But you can’t be pulling in that much data and not expect it to have an overall impact on network performance.”
As big data projects move from the planning to the implementation stage, many companies learn that they aren’t prepared for all of the changes that these projects bring. Big data by definition involves very large quantities of unstructured data in various formats that often change in real time. Because big data encompasses so much information in so many formats that must be pulled together for analysis, it has significant impact on enterprise networks and IT infrastructures. These range from resources and equipment to deployment and management.
Adding to the challenge is the fact that big data projects tend to be initiated high up in a company’s hierarchy. As a result, network managers and IT administrators are often left to deal with these issues once a project is already underway—in other words, once it’s too late.
This creates the potential for a worst-case scenario: A big data project fails to reach stated goals because the necessary IT resources aren’t available to support it, and the project strains the organization’s network and servers to the point that other operations and processes suffer.
According to a survey conducted by the Aberdeen Group that was published in July 2013, the impact of big data on enterprise networks was ranked as the No. 4 performance concern by respondents, the majority of whom said their organization had already implemented big data projects or planned to in the next 12 months.
Big Data in the House
The impact that big data has on enterprise networks and IT infrastructures is multidimensional and driven by the three Vs: volume (growing amounts of data), velocity (increasing speed in storing and reading data), and variability (growing number of data types and sources).
Here’s where you’ll feel it the most:
Bandwidth
Running big data analytics requires a lot of bandwidth on its own; the issue is magnified when big data and day-to-day application traffic are combined over an enterprise network.
Latency
The real or near real-time nature of big data demands a network architecture with consistent low latency to achieve optimal performance.
Capacity
Massive amounts of highly scalable storage are required to address the insatiable appetite of big data, yet these resources must be flexible enough to handle many different data formats and traffic loads.
Processing
Big data can add significant pressure on computational, memory, and storage systems, which, if not properly addressed, can negatively impact operational efficiency.
Big data projects combine sensitive information from many sources like customer transactions, GPS coordinates, video streams, and more. All of these must be protected from unauthorized access. Each of the above requires consideration and evaluation before embarking on a big data project. All too often, the process of evaluating and understanding the capabilities of the enterprise network and IT infrastructure doesn’t occur until a big data project is underway and a problem is encountered. “What often happens is people in the organization take the network for granted, so they just expect that a big data project will work,” says Brad Reinboldt, Product Marketing Manager with Network Instruments. “When it doesn’t, the business is impacted, and it’s the network managers who people come looking for.”
For more information on how your team can prepare for the impact of big data, get the free white paper, 4 Steps to Surviving Big Data.
Thanks to Network Instruments for the article.