How Data Analytics Helps Data Centress Reduce Downtime and Improve Operational Visibility

The modern data centres are the beating heart of our digital world. They need to operate 24/7, without any downtime, as downtime at data centres leads to website outages, halted transactions, and the loss of millions of dollars for companies.

With such high stakes involved, there is enormous pressure on data centre operators to ensure the perfect operation of their systems. However, maintaining uptime is getting tougher with each passing day. Data centres are getting larger, workloads are becoming heavier, and energy costs have become astronomical.

Thus, to overcome these issues, modern-day data centres are shifting away from the old and inefficient methods of reactive maintenance. They are now leveraging data analytics for data centres to ensure total visibility into operations and prevent downtime.

Why Are Data Centre Operators Struggling with Operational Visibility?

Very few data centres struggle with collecting data. To be exact, there are data centres that collect millions of data points every day. What makes this process difficult is converting these numbers to operational intelligence.

At some data centres, there are distinct groups who have completely different systems that they use to get things done. The engineering team has one system for power lines, while the maintenance team has another system that tracks the status of repair work. Lastly, the IT team has its own dashboard for tracking server performance.

The reason for this is that important details are being held back inside separate and isolated systems. This creates operational blackouts:

• Disconnected Information: It becomes hard to connect what happens on one side of the centre to the other, like the connection between a small power failure and a cooling unit.

• Manual Reporting: Spreadsheets and manual reporting means that the human eye only sees information after the problem occurs.

• Reacting vs. Acting: With no visibility of what is going on, the focus shifts to putting out fires rather than preventing them.

This is a frustrating experience for operation managers everywhere because it means less efficiency, more costs, and unnecessary downtime.

The Role of a Data Centre Building Management System

In order to keep tabs on the physical infrastructure of a building, there is a need for a data centre building management system. It is the nervous system of the physical structure. This system connects to thousands of sensors that monitor the health of the electricity and mechanics.

Even though the data centre building management system is very good at collecting the information, simply showing this information is not good enough. The true business advantage lies in using data analytics on this information to make instant decisions.

Why Data Integration is the Missing Link

Numerous data centres purchase costly analytics solutions but cannot see their benefits. The reason for this is not related to the analytics solution itself, the issue lies within data fragmentation. Insights remain invisible because valuable data is held by different silos such as IoT devices, maintenance systems, and energy meters.

In order to address this challenge, a data integration platform should be developed for the facilities. Such a platform serves as a universal tool for collecting information from all building automation systems, applications, and machines.

Designing this system may become a challenging process due to the high level of complexity. In this case, hiring experienced data integration consultants is considered a strategically sound decision.

These professionals know how to connect old machinery with cloud analytics safely. They will ensure the proper functioning of the data flow across the company network.

Analysing Incidents, Energy, and Equipment

After setting up a data integration framework, more sophisticated analytical algorithms can take care of all the hard work. AI works around the clock, analysing any events, energy usage, and equipment whatever relates to electrical or mechanical processes (for example, if some machine stops working, it turns into an event).

By combining these three aspects, data centres will be able to reach maximum efficiency:

Equipment Analytics (Predictive Maintenance)

Physical assets such as chillers, cooling pumps, and backup power generators almost never stop working without any previous symptoms. Before the breakdown happens, small, but noticeable signs appear: the machine vibrates slightly more, consumes more electrical energy, or warms up a few degrees.

The analytics engine learns how a machine should work when in perfect condition. Once an asset starts to show deviations from the baseline, the AI detects it immediately. Thus, the technician can perform targeted maintenance weeks before a machine fails completely, extending the asset's life and preventing costly downtime.

Incident Analytics (Rapid Resolution)

When any machine fails or falls below acceptable performance standards, it is regarded as a valid operational incident. The process of investigating the cause of an incident takes many hours through manual analysis in the case of a conventional data centre.

The use of analytics enables the system to analyze the behavior pattern of historical data. This allows it to detect the causes of machine failure instantly and also determine the necessary components required for its repair.

Energy Analytics (Cost Optimisation)

The amount of energy consumed by data centres is enormous, and a significant chunk of this energy is used only for cooling purposes. Energy analytics tracks the power distribution in all the systems on the fly. They detect the waste of energy, inefficiencies in machines, and guide users to efficiently use resources.

Transforming Operations with PleoData and PleoService

The creation of a trustworthy analytics ecosystem calls for specialised solutions that are able to recognise the peculiarities of industrial machinery operation. These are provided by PleoData to give business owners a comprehensive 360-degree analysis.

Rather than compelling users to buy costly pieces of hardware, the PleoData solution will work with the BMS of the data centre you have. It combines on-site equipment operation with AI analytics in the cloud.

At the very core of PleoData operations lies PleoService, which is an AI-driven solution for facility management and IT Service Management (ITSM).

AI-Enhanced Facility Management

PleoService leverages Generative AI Assistants to examine the continuous stream of information flowing in from your electrical and mechanical devices. In case an AI detects a machine anomaly or mechanical incident, it does not only set off an alarm. 

The system intelligently creates a ticket for an intelligent incident. It then assigns the problem to the appropriate technician, identifies an optimal course of action to take, and strictly manages operations' SLAs.

Driving Total Operational Team Accountability

Using PleoService, managers can monitor all incidents, time spent in repairs, and costs associated with maintenance within a single dashboard. It automates the need to manage spreadsheets manually, giving management total accountability of team performance.

Proactive Protection with PleoMaintenance

For best results, PleoService goes together with PleoMaintenance, which is PleoData’s Computerized Maintenance Management System (CMMS). In addition to being responsible for handling real-time incidents and creating tickets, PleoService

works in conjunction with PleoMaintenance, where all preventative maintenance and checklist information gets stored. Thanks to the combination of PleoService and PleoMaintenance, the system operates like an automated infrastructure safety network. 

How to Begin Your Data Centre Modernisation Journey

Switching to proactive management is always a process. There is no need to completely redesign the entire infrastructure to benefit from PleoData’s solution. The most logical step to take is to choose the biggest problem within your facility first.

1. Whether it concerns the group of outdated cooling units or the lack of cohesive energy reporting, focusing on solving it will help showcase the benefits of the system to other stakeholders in your facility.

2. By targeting one critical area for data integration first, your facility can prove the value of analytics early, secure team buy-in, and scale up the platform smoothly without interrupting daily operations.

Final Thoughts

It is not feasible for modern data centres to work with any sort of operational blind spots. This would lead to costly equipment breakdowns and unplanned downtime because of reactive approaches and disconnected building management systems. 

To implement data analytics for data centres via the best data integration solution, you need PleoData and PleoService. Through collaboration with PleoData and the implementation of PleoService, you can connect legacy assets, track incidents automatically, and improve the health of your equipment with the help of artificial intelligence.

At PleoData, innovation meets intelligence — from enterprise-wide workflow automation to streamlined data analytics consulting that turns information into insight. Our expertise extends from Power BI consulting services to end-to-end Microsoft Fabric implementation, ensuring your systems integrate smoothly. Backed by advanced incident management system and Gen-AI facility management solutions, we empower businesses to achieve full digital maturity. Whether it’s developing enterprise-grade apps with our Power Apps developers or optimizing IT operations through ITSM system, PleoData drives transformation at every layer. Make decisions from your raw facility data instantly.

Frequently Asked Questions

What is the difference between a BMS and a data integration platform?

A BMS keeps track of each machine individually. A data integration tool will combine information coming from the BMS, IT systems, and maintenance reports into one single screen.

Do we need to buy new hardware to use data analytics?

No. Advanced software integrates into your current system and uses data that is already being collected by your machines.

How does data analytics reduce human error?

Data analytics eliminate the use of spreadsheets completely and automate everything through the software. This software will monitor the machines around the clock and create tickets if any problems arise.

Can analytics work with older, legacy machinery?

Yes. Legacy and older equipment can be supported using special software bridges and API layers, allowing for collection of data from older machinery without having to replace anything.

What counts as an "incident" in facility operations?

An incident occurs if there is a failure of the equipment and/or if the equipment falls beneath its performance baseline, e.g., an overheated chiller or a malfunctioning power supply.