Data-Driven Analytics for Modern Data Center Decision-Making

Relying on “data analytics” is a critical flashpoint of business decision-making for modern data center operators. Analyzing data from compute, network, and storage provides patterns and trends–and a range of valuable insights from millions of data points critical to the operation of a portfolio. This allows operators to use fact-based data to turn insight into logical predictions rather than impulse or guessing games.

However, isolated and siloed raw data from existing IoT devices and in- building systems is worthless. Data transforms into gold when aggregated and analyzed in real-time to provide a historical context into the data center operations. From Edge to hyper scale data centers, IoT platforms not only allow real-time access to data but also transform raw data into actionable outcomes that owners and operators can leverage to optimize decisions and adapt to business changes over time. 

With access to a range of actionable analytics, data center managers and operators can optimize energy usage across facilities, improve automated occupancy rates, and pre-empt equipment maintenance to prevent costly expenditures and business operations disruptions.

The global big data analytics market is worth $307.52 billion. Nearly 92% of organizations say they “achieved measurable value” from their data analytics investments this year, and 3 out of 5 organizations rely on data analytics to drive their business innovation. 

When data is collected and analyzed, actionable data benefits facilities management, financial stakeholders, and end customers. Leveraging data analytics to expedite sound business decisions makes investments in data aggregation platforms worthwhile and provides actionable analytics, including:

• Predictive Analytics helps forecast future trends or outcomes based on aggregated historical data and statistical algorithms–for anticipated product demands, customer behavior, and emerging market trends for proactive decision-making.

• Descriptive Analytics summarizes the facility's historical data and offers visibility into past events so operators can quickly generate reports to gain an overview of key performance indicators (KPIs) and trends specific to their facility.

• Diagnostic Analytics identifies why specific events took place to provide a better sense of certain causes, problems, and outcomes–powering informed business decisions to address issues.

• Prescriptive Analytics provides a set of recommended actions to optimize business outcomes and enable data-driven decisions by mapping out the best actions to gain desired results.

• Machine Learning and Artificial Intelligence (AI) algorithms help analyze large datasets, identify patterns, and make predictions to help automate decision-making processes.

• Operational Analytics monitors and optimizes daily business operations in real-time and provides steps for improved efficiency, helps identify bottlenecks and automates responses to changing conditions.

• Risk Analytics evaluates potential business risks with a deep dive analysis of historical data that helps predict future risks and mitigate and manage risks associated with financial investments.

Mastering data-driven business decision-making takes time. Learn how market-leading software empowers data center operators with market-tested solutions that power actionable, expedited business decisions at a fraction of the cost.

 

 

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