Big Data Analysis and DCIM: Enhancing IDC Operations

Before the era of the Internet, mobile connectivity, big data, and cloud computing emerged, leading to the rapid construction of hundreds of data centers that generate massive amounts of data influencing daily life.

Just as map services rely on traffic data and e‑commerce platforms use consumer data, IDC (Data Center) operations also require extensive data analysis to ensure efficient and reliable service delivery.

1. IDC Operations Need Big Data Analysis

An IDC provides the environment for electronic equipment, integrating power, cooling, networking, and other facilities to support IT devices. Its complex ecosystem includes software, virtualization, servers, storage, disaster recovery, ventilation, fire protection, power distribution, logistics, security, and cost management, all of which generate diverse data streams.

Data sources include power monitoring (diesel generators, UPS, PDU), cooling systems (chillers, water pumps, PUE, WUE), fire and security monitoring, and ITSM systems. While some data are already visualized in reports, much remains at the raw collection stage, limiting cross‑system insights such as correlating a chiller fault with electrical anomalies.

Therefore, IDC operations urgently need big data capabilities for cross‑system integration, correlation, statistical analysis, and mining.

2. DCIM as an Effective Big Data Analysis Tool

Data Center Infrastructure Management (DCIM) bridges the gap between facility infrastructure and IT equipment, providing a unified platform to monitor, measure, manage, and control both physical and logical resources.

According to Gartner, DCIM tools monitor utilization and energy consumption of IT equipment and facility components. The 451 Group adds that DCIM collects asset, resource, and operational status data, which is then integrated and analyzed to help managers meet business goals and optimize performance.

In essence, DCIM unifies site facility infrastructure (power, cooling, fire protection, etc.) with IT infrastructure (servers, storage, networking), enabling comprehensive data analysis.

3. Value Delivered by DCIM to IDC Operations

3.1 Reliable Operations – DCIM records and analyzes fault data, allowing prediction of equipment failures and early warnings. By aggregating data from power and cooling subsystems, DCIM can identify abnormal trends (e.g., sudden increase in battery fault rate) and prompt preventive maintenance, reducing downtime.

3.2 Green Energy Savings – Energy consumption accounts for roughly 20% of national electricity use. DCIM’s cross‑system analytics help optimize cooling strategies, such as adjusting wet‑bulb temperature setpoints for natural cooling based on real‑time load, thereby lowering PUE and overall power usage.

3.3 Decision Support – DCIM provides integrated metrics for Space‑Power‑Cooling (SPC) management, enabling precise calculation of available rack space, power, and cooling capacity. This supports capacity planning, cost reduction, and architectural optimization (e.g., reducing redundant power feeds when reliability is proven).

Overall, DCIM transforms isolated monitoring data into actionable insights that improve reliability, efficiency, and strategic planning.

4. Future Outlook of DCIM Big Data Analysis

DCIM can expand into cost management, work‑order management, capacity management, reliability management, and energy‑billing integration. By linking fault alerts with emergency procedures, asset data with capacity planning, and knowledge bases with operational manuals, DCIM evolves into a comprehensive management platform.

5. Conclusion

Big data analysis is the core competitive advantage for IDC operations. DCIM is an indispensable tool for extracting, integrating, and analyzing this data, enabling energy savings, cost reduction, risk mitigation, and informed decision‑making. IDC operations are entering a data‑driven era where DCIM will be essential.

References

[1] Market Trends: Total Addressable DCIM Market Will Reach $1.7 Billion by 2016. Federico De Silva. Gartner 2012

[2] Datacenter Barriers. IDC Global DCIM Survey. 2012

[3] Operational sustainability and its impact on data center uptime performance, investment value, energy efficiency and resiliency. Vince Renaud et al. UPTIME

[4] DCmarketScape: Worldwide Datacenter Infrastructure Management 2013 Vendor Analysis. IDC 2013

[5] DCIM market size and forecast: onward and upward, 451 Group, 2012

[6] Thermal Guidelines for Data Processing Environments (ASHRAE TC9.9). ASHRAE Technical Committee, 2011