Friday, May 17, 2024

The Data Revolution: How Analytics Drives Data Center Efficiency and Operations

In an era where algorithms delve deep into our digital footprints, deciphering our behaviors and preferences, it is no surprise that data has transformed into an invaluable asset in the last few years. Many liken data to currency in this new age, an important resource that allows organizations to remain competitive in an ever-evolving digital landscape.

It is evident that the growing significance of data analytics cannot be ignored. Analytics is key in gleaning actionable insights from the deluge of data that organizations sift through, emerging as the bridge between raw data and informed decision-making.

Statista estimates that the big data market could grow up to 180 trillion gigabytes by 2025 — the storage capacity equivalent to 72 million human brains! Yet, despite the large amounts of data generated and collected each day, research also shows that over 68% of data goes unutilized by corporations. The staggering amount of untapped data represents missed opportunities and potential, but also serves as a resounding call for organizations to seek more efficient ways — such as robust data centers — to harness and master this invaluable resource.

Data centers as the focal point of data analytics

Today, data is more prevalent than ever. With every touch of a button, mouse click, and swipe on a screen, data is generated with each interaction, giving rise to a digital tapestry of information that exists online. As data creation continues to grow with the proliferation of digital services, this has inevitably led to the mounting need for data centers that excel in effectively managing and processing these vast data quantities.

Demand for data centers has surged in recent years, with Cushman & Wakefield’s latest report highlighting how the accelerating digital economy has driven the growth and expansion of the data center market, especially in Asia Pacific. In fact, in Singapore alone, the data center market is expected to exceed one gigawatt in 2024. This has inevitably created a growing need for more efficient and reliable data center infrastructure, as governments and organizations look for sustainable ways to fulfill demand for more computing power.

Yet, expanding and optimizing data center operations isn’t as straightforward as simply adding on new equipment. Piecemeal upgrades over a long span of time can result in an unnecessarily complex environment, where data center teams have to deal with a mix of hardware and software from multiple vendors, and try to gauge the remaining lifespan of aging technologies. Besides technical integration issues, manpower challenges may include a lack of coordination between facilities and IT teams, and difficulty finding talent due to the ongoing skills shortage globally.

While costs and agility are perennial issues for any business, server downtime and power outages have increasingly costly implications as businesses move online. This can range from the loss of potential revenue, bruised reputation to equipment damage. How then, can the expansion and enhancement of data center infrastructure be facilitated smoothly?

Convergence of AI and analytics

There is a huge opportunity for AI-driven analytic and power management systems to step in and plug this gap. These technologies have potential to create positive and lasting change in addressing the traditional challenges that have plagued how data center operations are managed. Already, over half of data center operators have considered utilizing AI to make routine operational decisions. By leveraging them to further enhance tools such as predictive analytics and automation, organizations will be well-equipped to support their evolving power demands, and enhance their resource efficiency and systems reliability for success.

The need for a clear, unified view of the entire data center infrastructure, across all physical and virtual components, is more critical than ever as businesses expand their computing infrastructure. It’s no longer just about asset optimization, but having the ability to automate, monitor and plan ahead through real-time data and analytics. This allows operators to assess the operational capabilities and limitations of their data center facility more accurately, reduce operational costs and ensure continuous uptime.

Beyond remote monitoring and management, AI-driven analytic systems are able to significantly simplify asset tracking and management workflows through functions such as 3D visualization, thermal mapping, and capacity planning. This better equips teams to plan for system upgrades, avoid unnecessary expenditures and support evolving power demands.

Additionally, AI will be able to enhance existing solutions like electrical power management systems (EPMS) that allow organizations to monitor power usage around the clock, and aid them in meeting their sustainability goals. AI-driven algorithms can optimize energy usage by adjusting cooling systems, lighting, and power distribution based on real-time conditions. Teams are also better able to forecast energy demand and consumption through predictive analytics and monitoring, and prioritize the use of renewable energy sources in the long run.

A new era of data analytics

As data proliferation only continues to grow, it is clear that data analytics has an indispensable role in maximizing the efficiency of data centers. Data centers that harness the full potential of data analytics to make strategic decisions are better equipped to meet the evolving needs of businesses, such as identifying real-time trends and patterns or safeguarding the integrity and security of the data they have. This ability will be key for organizations to continue leveraging the wealth of information at their disposal, and remain at the forefront of a smarter and more connected world.