Data Center Challenges with Big Data

Data Centers Challenges with Big Data

Data Center Challenges with Big Data

Overview: Big data comes with big challenges. The data will keep on expanding with a tremendous velocity. The study has shown that almost 90 percent data has been generated in the last two years, so the challenge is to handle this huge volume of data. The data explosion has to be supported by the data centers.

In this article I will talk about the impact of data explosion (which is big data) on the data centers.

Data centers are of immense importance while we consider big data and its storage. In one side, data explosion gives us an opportunity to get more insight; on the other hand, it brings lot of challenges. One of the biggest challenges is to manage the storage of data, which is data center management.

Must Read – How Big Data Can Revolutionize Healthcare Sector? 

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

Electrical infrastructure: 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 capable of taking huge volume 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 has to be enhanced or a new infrastructure needs to be deployed. Organizations are taking lot of initiatives to measure the suitability of their existing electrical infrastructure and future expansion plan. Reliability of electrical infrastructure is also important while considering data volume and its processing. 

Must Read – How Big Data is changing the world of Data Recovery Services? 

Electrical Power and cooling: Big data has an indirect impact on the 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 demand of big data has a cascading effect on power demand and cost. Data center managers are planning for future power consumption and its associated costs. The location of data center is also important for cost estimation. The current trend is to move the data centers to remote locations away from metro cities. Cooling cost is also an important point to remember, because it is approximately 30% to 40% of the total power cost. In most of the cases data centers are moving towards northern part, as the demand for cooling is much lower due to its cool climate year around. 

Must Read – Pairing of IOT and Hadoop 

Storage infrastructure: Big data will also impact data center storage infrastructure. Earlier these data centers were used to store relational data, but now the data centers are supposed to store different types of data (like structured, unstructured and semi structured etc.). So the storage infrastructure has to be enhanced to support and store huge volume of data (known as big 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 are making proper storage plan to support big data. 

Must Read – Why Apache Spark is the future platform for big data?

Chang in traffic pattern:  In big data, the data sources are different. The type, volume and format of data are also different. So there is a change in overall data pattern. Earlier the data centers were designed to store data of specific format, but now it is difficult to understand the pattern itself. This change in data traffic pattern is one of the major concerns. 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 the data center storage. The data center storage architecture has to be compatible with new data format. Organizations are continuously innovating new ideas to manage the data center with big data load. 

Must Read – Why Python is important for big data?

Security: Data center security will be another major factor impacted by 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 in data centers, because it contains the confidential information of an organization. Organizations are working on different approaches to avoid security threats. Data center security has to be implemented at 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. 

Must Read – Big data and cloud computing – What you don’t know! 

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 band width requirements. Because the applications were interacting with data centers through human generated requests only. These human generated requests are comparatively small in volume compared to volume of big data in-flow. Big data sources will send huge volume of data to these data centers which will increase inbound band width requirements. So the data center network infrastructure has to me modified/upgraded to support the volume and velocity of data. It will also increase the band width requirement of the network.

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So there are different big data factors which impacts data centers worldwide. The major challenges are electrical infrastructure, power and cooling. The other impacts are related to data center storage, network, data pattern and security. As big data is continuously evolving, it will come with new challenges. So the future data centers need to be designed keeping all these factors in consideration.

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