Four Key Digital Technologies for Data Centre

Written by Shereen Chan See Yen, PDPM

Four Key Digital Technologies for Data Centre

Written by Shereen Chan See Yen, PDPM

by Shereen Chan See Yen, PDPM

Data Centre industry is very competitive nowadays with a growing number of data centre operators in the region that are able to provide a more comprehensive suite of services to support enterprise requirement. In order to compete and stand out from other data centres, besides focusing on its product and services offerings, the data centre has to adopt new technologies to optimize the resources they have to improve data centre efficiency, productivity, and security.

Artificial Intelligence (AI)

AI is the technology enabling machines to learn from experience and perform human-like tasks. AI systems perform intelligent searches, interpreting both text and images to discover patterns in complex data, and then act on those learnings based on mountains of data created by humans. Nowadays, AI is influencing the development of modern data centres. With the surge in the amount of data every day, traditional data centres will eventually get slow and result in an inefficient output.

Data centre operators can drive efficiencies up and cost down by using AI in many ways. There is also a trend that future data centre will apply face recognition AI technology for data center security. As an example, Google uses the Google DeepMind system to significantly improve the power efficiency of its data centre. The system makes all the cooling-plant tweaks on its own continuously. It can help companies achieve saving up to 30% of the plant’s energy annually. This showed that companies can significantly reduce their energy-related costs using AI.
The picture below shows how the company uses AI software from LitBit to automate the management of data center facilities.

Data Analytics

In today’s big data era, data is growing at unprecedented speed. Data is the company’s most valuable asset. Data analytics is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions.

There are 4 types of data analytics we encounter in data science, namely Descriptive, Diagnostic, Predictive and Prescriptive.

• Descriptive: What is happening?

Descriptive analytics is designed to get us basic expository information: who, what, when, where, how many? It is the backbone of reporting—it’s impossible to have BI tools and dashboards without it.

• Diagnostic: Why is it happening?

Diagnostic data analytics is the process of examining data to understand cause and event, or why something happened. Techniques like drill-down, data discovery, data mining, and correlations are often employed.

• Predictive: What is likely to happen?

Predictive analytics is used to identify trends, correlations, and causation. It utilizes statistical algorithms and AI-driven machine learning techniques to analyze data gathered over time to anticipate future outcomes.

Types of Data analytics

Picture illustrating the different types of Data Analytics and taken from https://www.kdnuggets.com/2017/07/4-types-data-analytics.html

• Prescriptive: What do I need to do?

Prescriptive analytics is where AI and big data meet to help predict outcomes and what actions to take. It can help us test the right variables and even suggest new variables with a higher chance of generating a positive outcome.
Data centres are undergoing constant changes because the needs of customers are constantly shifting. Companies frequently spin their computing and data storage requirements up or down based on demand from customers. To prevent any knockdown effect throughout the facility’s infrastructure, simulation programs driven by predictive analytics can solve this problem.

These programs run through model-based simulations that take into account a variety of complex variables. It can anticipate how moving equipment will affect heat dispersion or network latency in a data centre. Technicians can then manage equipment and services with minimal disruption. By flagging potential issues, predictive analytics simulations can also help to avoid major problems that would otherwise require significant time and effort to troubleshoot and resolve.

Augmented Reality (AR)

AR is the overlay of digital content on the real-world environment. When one sees the real world supplemented with digital objects, that is AR. AR layers digital information and/or data on top of a user’s view of the real world. It might be something as simple as text notifications or Internet search information delivered through a wearable device or as complex as delivering personalized marketing content to consumers through sensors to a smartphone.

With Tablets and Smartphones taking a prime spot in an average employee’s workday, there are growing applications for using interactive mobile applications integrated with contextual AR features to provide some cool performance support applications. A data centre can use AR to know how many server racks they can keep and test in the staging rooms before moving the tested racks to data hall safely and securely.

For example, IBM is using AR for its data centre projects. It involves the usage of AR for providing information about each asset overlaid on top of the asset on the device. This information could show data like temperature, memory usage, and any other critical information.

Virtual Reality (VR)

In the world of Virtual Reality, or VR, users experience artificial sounds and sights and feel as if they are in a digital world. Unlike traditional user interfaces, VR places the user inside an experience. Instead of viewing a screen in front of them, users are immersed and able to interact with 3D worlds.

When a company chooses a data centre or colocation provider to house their company’s critical IT infrastructure or data, the sales representative will conduct a data centre tour for their customers. By using a VR headset, customers can experience a Real-Life 3D data centre tour in 360 degrees as a real, continuous, and virtual scene. Data centre can also use VR to perform disaster recovery exercise to simulate a disaster recovery process.

RagingWire Data Centre is the first data centre colocation company that offers a real-life and true stereoscopic 3D virtual reality (VR) tour of a data centre. From the networking room to the cooling towers outside of the facility, customers can explore the different areas of the data centre in the guided video tour. What they need to do is just putting on a VR headset. The ‘Real-Life 3D’ VR tour offers the depth and space of the actual data centre and gives users complete control over their exploration of the environment.

Conclusion

Technology is an ever-evolving and ever-influential part of our everyday lives. It is advancing so quickly that it can be difficult for us to predict what is coming next. Businesses including data centre operators have to make use of the new technologies that are available in the market to improve data centre efficiency. Many data centres operators are already using AI and Data Analytics but not all of them are using AR and VR tools. They have to start to understand how their customers think and discover their preferences in terms of using AR and VR. All of this will ultimately have an impact on the supply chain.

Augmented Reality in the Data Center


References

Ali Marashi. (2018). “Building a Better Data Center with Predictive Data Analytics”. Retrieved from https://www.vxchnge.com/blog/building-a-better-dwata-center-with-predictive-analytics, accessed 23/06/2019.

Melisha Dsouza. (2018). “How AI is going to transform the Data Center”. Retrieved from https://hub.packtpub.com/how-ai-is-going-to-transform-the-data-center/, accessed 23/06/2019.

Raging Wire. (2016). “RagingWire launches Immerse “Real Life 3D” Virtual Reality Tour Of Its California Data Center”. Retrieved from https://www.ragingwire.com/news/ragingwire-launches-virtual-reality-tour-of-california-data-center, accessed 23/06/2019.

Ruth Ng Yin Fun, ADPSM. (2019). “Data Analytics and Artificial Intelligence for Cognitive Procurement”. Retrieved from SIPMM: https://sipmm.edu.sg/data-analytics-artificial-intelligence-cognitive-procurement/, accessed 23/06/2019.

Shun Huang. (2017). “Brief Introduction of Data Center Technologies”. Retrieved from https://www.codeproject.com/Articles/1181824/Brief-Introduction-of-Data-Center-Technologies, accessed 23/06/2019.

Susan Tan, DPSM. (2018). “The Impact of Virtual Reality and Augmented Reality (AR) ” on Procurement. Retrieved from SIPMM: https://sipmm.edu.sg/impact-virtual-reality-augmented-reality-procurement/, accessed 23/06/2019

Thomas Maydon. (2017). “The 4 Type of Data Analytics”. Retrieved from https://www.kdnuggets.com/2017/07/4-types-data-analytics.html, accessed 23/06/2019.

About the Author: Shereen Chan has several years of experiences in the field of procurement, specifically in the telecommunication industry. Shereen is a member of the Singapore Institute of Purchasing and Materials Management (SIPMM). She holds a bachelor’s degree (honors) in Tourism Management and Engineering. She completed the Professional Diploma in Purchasing Management (PDPM) in June 2019 at SIPMM Institute.

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