3 Key Infrastructure Considerations For Your Big Data Operation

Within this special guest attribute, AJ Byers, President and CEO, ROOT Data Center, indicates that if your organization is launching or expanding a Big Data adviser, it would be wise to maintain the needs of real estate, electricity and up-time top-of-mind. Whether your Big Data operations reside on-premises, in a colocation data centre, or at the cloud, infrastructure that is dependable, scalable, sustainable and adaptable is ground zero for ensuring its success. AJ Byers has 20 decades of experience in the data center market. Recently, in the development of one of Canada’s largest data center service companies with 15 centers he led the team as president of Rogers Data Centers nationally. He has long been a pioneering force in the business. As COO in Magma Communications, he was instrumental in building one of the very first data centres of Canada.


Big Data has and continues to form huge businesses worldwide. It’s transformed the way business decisions are made in the financial services, health care, retail, and manufacturing businesses, in addition to others. Less examined, however, is its impact on the data centre market. As more and more information is generated, stored, and analyzed servers will be needed. Where and how these servers are saved and managed to keep to keep up-time and empower high performance operations is a consideration. So too are more physical space and power that is dependable, as Big Data operations increase and more servers are required.

Although the cloud feels to be an ethereal place, we do well to remember that the cloud is really just another person’s server area — topic to the same demands of power and connectivity. So, whether Big Data operations exist on-premises for a company, in a colocation data centre, or at the cloud, then IT operators need to ensure their infrastructure needs are met today and in the future. Real Estate

Servers demand physical distance, irrespective of their deployment in colocation facilities or at the cloud. Real estate is becoming a limiting factor for Big Data operations and expansion due to its scarcity as data centers move closer and closer to population centers.

When it comes to growth possible, be mindful of not only the financial stability of this data center provider, but in addition its access to the brown and greenfield property, flexible infrastructure for scalability and deployment speed. Ability

Based on IBM, 2.5 quintillion bytes of information are created daily and 90 percent of all the data on earth was produced in the last couple of years. This pace is reflected in data center growth. According to JLL’s 2017 Data Center Outlook report, the U.S. saw a listing 357.85 MW absorbed — a continuation of what JLL calls for the”still uncontrolled momentum” that characterizes data center usage globally. In addition to general electricity, electricity per server’s density is increasing. Not long ago, 2kW per rack was average; densities of 30 or 40 kW per rack are required and today, that’s barely minimum.

As you plan for your company and its IT infrastructure to grow, you should also ensure that your data centre has access to available power rather than all grids can provide MWs on demand. The data center also has to be able to cool high density racks which is a comparatively new industry requirement. Another vital consideration is to make sure that your operator offers innovative technologies that reduce your carbon footprint and electricity consumption if your company values data centre sustainability. Up-time

Expectations for Big Data surgeries have to be an”always-on” scenario. When”two minutes is too late” is the modus operandi for Big Data, the underlying requirement is 100 per cent up-time for its infrastructure. From the data centre environment, in the cloud or whether collocated, up-time is reached through redundant design. Electricity from the local utility is backed up instantaneous switches and by generators in the event of an outage. One-hundred percent uptime is attainable, but threat remains. While redundancies can be constructed in with extra generators and switches, these come in large capital cost.

Emerging trends in downtime risk reduction come in the usage of artificial intelligence (AI) and machine learning to maintain operations in their highest possible performance. Google first utilized factors to be tracked by AI and calculate efficiency at 2014 at its server farms. Other wholesale information centers utilize AI and machine learning to decrease the danger of information center down-time. The integration of AI to the colocation uk ecosystem is intended to work alongside staff, combining technology and people. Data centres can leverage AI characters and machine learning sensors educated by data centre technicians to identify indicators that a collapse is possible.

If your organization is launching or expanding a Big Data initiative, it would be sensible to keep the needs of property, electricity and up-time top-of-mind. Whether on-premises live, in a colocation data center, or infrastructure that’s dependable, scalable, sustainable and adaptable is ground zero for ensuring its success.