Data centers and AI: 3 major challenges in the colocation market

The fourth industrial revolution is giving rise to a data culture for accelerating digital transformation. Organizations are deploying data-driven business models to utilize the maximum potential of data. Since every organization has started implementing aggressive data collection and analysis models for various applications, they are also deploying large data centers for its storage and processing.

Datacenter operations require a skilled workforce, which can become a costly affair for many companies. However, opting colocation data center can solve these problems instantly. As an alternative to traditional data centers, colocation offers many advantages, including AI-based operations.

Leveraging AI (artificial intelligence) may seem feasible for data-driven companies, but the colocation data center industry faces a set of challenges that must be resolved.

• Instrumenting the Data Centers

Smart technologies like Artificial Intelligence and Machine Learning are only a foreign concept to traditional data centers. Modern colocation centers generally use such technologies to run and maintain data center operations. Primarily, data centers with DCIM suit perform better in this regard. However, instrumenting data centers also falls on equipment vendors as they must make sure adequate working of AI algorithm. 

Digitizing equipment like UPS, cooling units, and switchgear can help solve the issue. As colocation data center providers increase the use of AI, deployment of supporting technologies also become essential. 

• Using Modern Tools

Building Management System (BMS) acts as the heart of a data center to easily manage AI-based operations. Electrical Power Monitoring System (EPMS), Data Center Infrastructure Management (DCIM) are some tools which help make operations easy and quick. For a system to understand all the critical variables and their interconnection, AI-based models help solve colocation data center challenges.

Considering all the disparate, utilizing complete data remains a challenge. Using modern tools like EcoStruxure IT can help protect critical information better, which ensures a data center’s physical infrastructure adapts quickly to support future demands driven by the use of artificial intelligence. Without any compromises, the IOT-enabled architecture and platform can help achieve the operational efficiency of a data center.

• Data Integrity

Every data collected from a colocation center must have some correlation and context for its full utilization. For a given dataset from a particular asset, the operational model can have a site, room, U-space, row, power path, network port, and policy requirement. 

DCIM tools require mapping out and defined things, which generally takes many efforts and resources for initial set up and maintaining dynamic tasks over time. It is also mainly upon the colocation center providers to simplify such complexities and provide a better solution to their tenants.

AI in Data Centers: What’s Next?

It is crucial to say that artificial intelligence is not going to solve all the challenges of a traditional data center while turning into a cutting-edge site with near-perfect PUE and record availability. The fundamental practice of a data center regarding design and operations is still crucial to success.

The use of artificial intelligence is slowly picking pace in the colocation data center industry. Having a well-implemented and maintained DCIM system is a crucial step for all colocation service providers. Such systems provide necessary metering and contextual data, which makes AI tools effective.

The benefits of artificial intelligence deployed in a colocation data center are significant. If you face any issues while learning the systems or what type of tools are available in the market, contact smart solution providers who specialize in such products and services. Moreover, you can also connect with their customer services for learning more about best-in-class solutions for business growth.

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