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How Big Data Impacts Data Centers


Data centers weren't originally designed to deal with the demands of big data. Here's what they need to consider when ensuring proper handling of big data.

Big data comes with big challenges. This type of data collection will continue to expand with a tremendous velocity. Studies have shown that almost 90 percent of all data has been generated in the last two years, so the challenge is to handle this huge volume of data. This massive data explosion must be properly supported by data centers.

Data centers are of immense importance when considering big data and its storage. On one hand, this data explosion gives us an opportunity to get more insight; on the other hand, the sheer volume of data brings significant challenges. One of the biggest challenges is to manage the storage of data, which is data center management.

Let’s have a look at some of the major impacts of big data on data centers.

Electrical Infrastructure

The electrical infrastructure of a data center is one of the major concerns for handling big data. The biggest question is whether the existing electrical infrastructure is capable of taking on such huge volumes of data loads. The answer is "no," because the huge data volume needs to be handled by a more robust electrical infrastructure. So the existing electrical infrastructure must be enhanced or a new infrastructure needs to be deployed. Organizations are taking initiatives to measure the suitability of their existing electrical infrastructure and future expansion plans. Reliability of electrical infrastructure is also important while considering data volume and its processing.

Electrical Power and Cooling

Big data has an indirect impact on data center power consumption. As the electrical infrastructure expands, the electrical power consumption increases many fold. How this power demand can be met is a big question. The power should be reliable, renewable, abundant and energy efficient in nature. So the demands of big data have a cascading effect on power demand and cost. Data center managers are planning for future power consumption and its associated costs.

The location of a data center is also important for cost estimation. The current trend is to move data centers to remote locations away from major cities. Cooling cost is also an important point to keep in mind, because it is approximately 30 to 40 percent of the total power cost. In many cases, data centers are moving toward northern climates, as the demand for cooling is much lower due to cooler year-round temperatures.


Storage Infrastructure

Big data will also impact data center storage infrastructure. These data centers were designed to store relational data, but now data centers are supposed to store different types of data (like structured, unstructured and semi-structured, etc.). So the storage infrastructure needs to be enhanced to support and store huge volumes of data. Big data has its own characteristics like velocity, volume, veracity and variety, so the data center storage infrastructure should be able to support these features. To overcome these complexities, organizations must make proper storage plans to support big data.

Change in Traffic Patterns

Big data relies on many different data sources. The type, volume and format of the data are also different, so there is a change in overall data pattern. This change in data traffic patterns is a major concern. To handle this new big data traffic pattern, data center engineers are thinking of innovative designs and their deployment. The change in traffic pattern also has a direct impact on data center storage. The data center storage architecture has to be compatible with the new data format. Organizations are continuously innovating new methods to manage data centers with big data loads.


Data center security will be another major factor impacted by the big data explosion. Big data is all about data, so its security at the storage level is a critical challenge to overcome. The data has to be secured because it contains an organization’s confidential information. Organizations are working on different approaches to avoid security threats. Data center security has to be implemented at the network level, storage level and also application level. As the data center infrastructure expands to support big data volume, security planning should be done to mitigate threats from all directions.

Data Center Network

Big data will also impact data center network infrastructure. The existing data center WAN (wide area network) links are capable of handling moderate bandwidth requirements. Because the applications were originally interacting only with data centers through human-generated requests, these requests were comparatively small in volume compared to the volume of big data inflow. Big data sources will send huge volumes of data to these data centers, which will increase inbound bandwidth requirements. Therefore, the data center network infrastructure must be modified/upgraded to support the volume and velocity of data. It will also increase the bandwidth requirement of the network.

There are different big data factors which impact data centers worldwide. The major challenges are electrical infrastructure, power and cooling. The other areas impacted are related to data center storage, network, data pattern and security. As big data is continuously evolving, it will continue to bring about new challenges. Therefore, future data centers must be designed with all these factors kept in consideration.


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Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…