Businesses must eliminate the unnecessary energy costs of data processing

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Among 70% and 90% of the data that organizations collect is considered “dark data” – that is, data that is unquantified and unused. Dark data is not converted into insights and business opportunities, but still leads to unnecessary energy costs. As data grows exponentially, these unsustainable data processing practices are a growing problem. More than 90% of the world’s data has been generated in the past two years alone, with data spreading across more devices, applications and cloud platforms and in more formats.

The exponential growth of data has the potential to result in increased energy demand and carbon emissions, which experts agree is significantly derailing global ambitions of zero and 1.5°C. Businesses must adopt a greener approach to data management to reduce storage requirements, generate energy savings and help meet global and local sustainability goals.

By identifying and removing unnecessary data, including dark data, redundant, obsolete, and trivial (ROT) data, and data outside of retention service level agreements (SLAs), companies can eliminate storage waste and reduce their overall data storage requirements. In other words, less storage translates into less energy consumption and CO2 emissions.

Reduce carbon intensity

Data centers are essential to moving our digital world forward — they support everything from video conferencing to smart cities — but they also require an exceptional amount of energy to function. With no argument to rid our world of data stores, we should instead focus on managing data to reduce their carbon intensity so they can work more efficiently, use less energy and emit less CO2.


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Sustainable data management calls on companies to adopt a more environmentally friendly cloud service and leverage edge computing by facilitating data movement and automation from anywhere. Average migrations from on-premises to the cloud can lead to 65% energy savings and an 84% CO2 reduction.

A data intelligence and automation platform can help businesses identify and delete unnecessary data, including dark data, ROT data, and data outside of retention SLAs, to eliminate storage waste and reduce overall data storage requirements. We’ve seen customers reduce their storage footprint by up to 40% simply by leveraging data intelligence and automation technology to turn their “data chaos” into intelligent information.

Increase storage durability

All data centers to generate the same amount of CO2 emissions as global airlines. This should be a wake-up call for the global business, policy makers and the public. Sustainable data storage needs to be implemented quickly because we know that our world’s data usage is growing exponentially.

Many organizations have what we call a “data swamp” or unmanaged data lake that offers little to no business value. Data swamps are so common because most data owners and IT departments can barely keep up with data storage, let alone take appropriate data quality and data governance measures. In addition, identifying the data that requires special attention is a highly manual process that often requires special skills, leading to compromising data security, compliance and data protection. High-value data is then mixed with waste data, making data analysis projects more difficult, time consuming and expensive.

However, automated data intelligence platforms can discover and classify all of a company’s data, no matter where it resides, giving IT back the power to better visualize and analyze the data that matters most to make more sustainable decisions about data storage.

Data Processing: Optimizing Data Migrations

Cloud vendors usually have higher CPU usage compared to individual companies, so they can charge more without increasing power consumption. A data intelligence and automation platform simplifies offloading data to the cloud to increase storage durability, and provides businesses with a seamless cloud data migration process. Businesses can reduce schedules, costs, risk and complexity of moving data by ensuring that only useful data sets are moved through automated cloud migration.

The more unstructured data a company has, the larger its data footprint. Businesses can become greener by identifying redundant, obsolete and trivial data. Unaccounted for data is harmful to the environment because it takes up space on servers and slows down processing. Companies are buying disk after disk to support data growth, but in five years they will run out of space and have accumulated a plethora of disks. This process is expensive and unsustainable, increases security risks and often costs companies millions.

Companies need to adopt a greener approach to data management to reduce storage requirements, generate energy savings and help meet internal and external sustainability goals.

Adrian Knapp is the CEO and founder of Devices

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