Machine learning applications can serve as a solid mechanism for data center optimization.
Artificial intelligence is growing and becoming more efficient and useful to incorporate data elements and managing data centers.
With technology becoming more advanced every year, it makes a lot of sense to use artificial intelligence to ensure any company is more effective and productive. AI is constantly updating and learning to make businesses better while lowering implementation costs at the same time. Google, one of the leading users of artificial intelligence, created an AI system to not only improve efficiency in data centers, but also to reduce costs.
AI Data Center
Google’s artificial intelligence system not only analyzes and guides business decisions, but also reduces the cost of cooling data centers by about 40 percent. The startup DeepMind analyzes over 100 different variables within the data center to improve efficiency and reduce power consumption. It also improves server cooling operations better, which, in turn, reduces associated costs. With a startup such as DeepMind implementing AI analytics, the cost has not only gone down to run data centers, but uptime has become faster while also increasing security.
Tier 4 Data Center
While a tier 3 data center has 99.982 percent availability, a tier 4 data center is even better. With a 99.995 percent availability, a tier 4 data center offers much more in the way of full redundancy. A tier 3 data center is not fully protected from outages a severe incident could cause, while a tier 4 data center is almost completely secure. A tier 4 data center is fully redundant and is protected from serious technical outages which allow the server to remain constantly available. A tier 4 data center also allows for a hot-swap of components, which means the server does not need to waste time by cooling down before a faulty component can be changed.
Data Science
Data science is a lot like data mining. This is when computers use their own power to extract knowledge or insights to find data patterns. Data science analyzes actual phenomena to understand and unify statistics. It is with data science that companies can market to their consumers better. Data science is used within a wide range of applications and uses the patterns and statistics it learns to make the application better. Data science, also known as data-driven science, is believed to be the fourth paradigm of science after empirical, theoretical, and computational paradigms.
Data Center Management
With data center efficiency being so important, the management of the data center is extremely critical. Data center infrastructure management, or DCIM, is a view of the data center’s performance. When analyzing the performance, administrators can see if energy, equipment, and floor space are all being used efficiently. DCIM usually implements a three-step process of monitoring details of the data center, first to analyze how to utilize the data center more efficiently and then automating for synchronized management.
Artificial intelligence is vastly becoming a necessity in our world. To be more knowledgeable and efficient, AI must be the same way. Between data science, data centers, and data center management, artificial intelligence is being used more and more by companies who want to obtain and maintain a competitive edge. Without proper implementation of AI, many companies (yours included) would fail.
