Why clean data is as important as clean energy
Zahl Limbuwala, Co-Founder & Executive Director
Renewable energy initiatives have been on the news agenda the last couple of weeks.
According to Bloomberg, a large proportion of the Fortune 500 has set clean energy goals in response to the savings generated by renewable power. As companies amass huge amounts of data, a significant part of their strategy for reaching their ambitious goals will involve data centers, no matter if a business owns, builds or uses them in the Cloud.
Apple is leading the way in this area. The company recently released its Annual Environmental Responsibility Report which provides a detailed outline of the steps it is taking to ensure its data centers are environmentally friendly.
Of course, in order to assess progress and success these companies will also need to track and report against sustainability and energy efficiency metrics too.
Accurate, reliable data is critical
But metrics are only as good as the accuracy of the data feeding into them. If companies put sustainability at the core of their business strategies, the metrics they set will be heavily scrutinized.
So, what happens if raw data from data centers is not properly cleaned and validated, leading to weeks and even months of incorrect and misleading information?
The result will be an embarrassing anomaly in the resulting operational report and a lot of awkward explaining to managers, stakeholders and potentially customers and shareholders.
Accurate, reliable data is central to a serious sustainability initiative; collecting raw data and presenting it is simply not enough. After all, important decisions about a facility’s environmental profile are made on the basis of that data, so it needs to be spot-on.
The key to meeting environmental goals with confidence is to collect, clean, validate and then analyze the data relating to energy efficiency, carbon emissions and water consumption, in order for the business to have confidence in it. In this way, data center managers can quickly understand what areas need adjustments and remove the risk of making poorly informed decisions due to bad data when planning changes or improvements for each facility.
Another crucial point for organizations with clean energy objectives is in the planning of data centers. A report containing incorrect data could lead to a design that struggles to meet the business requirements, or to large budgets being spent without a verifiable return on investment . Analysis of available data can help to ascertain the most economic, sustainable and cost effective design options and locations before a spade even hits the ground.
It is reassuring to see so many renewable and environmentally-minded projects being initiated by world leading organizations. Let’s hope they pay as much attention to clean data as they do to clean energy.