Businesses need to eliminate unnecessary energy costs from data processing
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Between 70% and 90% of the data collected by organizations is considered “dark data”, that is, unquantified and untapped data. Obscure data is not transformed into information and business opportunities, but it still leads to unnecessary energy costs. As data grows at an exponential rate, these unsustainable data handling practices are a growing problem. More than 90% of global data has been generated in the past two years alone, with data spanning more devices, apps and cloud platforms and in more formats.
The exponential growth of data has the potential to drive increased energy demand and carbon emissions, which experts say significantly derails global net zero and 1.5°C ambitions. Businesses need to take a greener approach to data management to reduce storage needs, generate energy savings, and help meet global and local sustainability goals.
By identifying and removing unnecessary data, including obscure data, redundant, obsolete, and insignificant (ROT) data, and data outside of retention service level agreements (SLAs), businesses can eliminate wasted storage and reduce their overall data storage needs. In other words, less storage translates to less energy and CO consumption.2 emissions.
Reduce carbon intensity
Data centers are essential to propelling our digital world forward – supporting everything from video conferencing to smart cities – but they also require an exceptional amount of energy to operate. Without an argument to rid our world of datastores, we must instead focus on how to manage data to reduce its carbon intensity so that it can operate more efficiently, consume less energy and emit less CO2.
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Sustainable data management calls for businesses to operate a more environmentally friendly cloud service and take advantage of edge computing by making it easier to move and automate data from anywhere. Average on-premises migrations to the cloud can result in 65% energy reduction and 84% carbon emissions reduction.
A data intelligence and automation platform can help companies identify and remove unnecessary data, including dark data, ROT data, and non-SLA retention data, to eliminate wasted data. storage and reduce overall data storage requirements. We’ve seen customers reduce their storage footprint by up to 40% simply by deploying data intelligence and automation technologies to turn their “data chaos” into intelligent insights.
Increase storage durability
Data centers already generate the same amount of carbon emissions as global airlines. This should be a wake-up call to global business, policy makers and the public. Sustainable data storage needs to be implemented soon, as we know that data consumption around the world is growing exponentially.
Many organizations have what we call a “data swamp,” or an unmanaged data lake, that offers little or no business value. Data floods happen so often because most data owners and IT departments can barely keep track of data storage, let alone create proper data quality and governance measures. Additionally, identifying data that needs attention is a highly manual process that often requires special skills, compromising data security, compliance, and protection. High-value data is then mixed with useless 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, wherever it resides, empowering IT to better visualize and analyze the data that matters most to take more sustainable data storage decisions.
Data processing: Optimizing data migrations
Cloud providers typically have a higher level of CPU utilization than individual companies, allowing them to compute more without increasing power consumption. A data intelligence and automation platform simplifies offloading data to the cloud to increase storage durability, providing enterprises with a seamless process for migrating data to the cloud. Businesses can reduce the time, cost, risk, and complexities associated with moving data by ensuring that only useful data sets are moved through automated migration to the cloud.
The more unstructured data a company has, the larger the data footprint. Businesses can go green by identifying redundant, outdated, and trivial data. Unaccounted data is harmful to the environment as it takes up space on servers and slows down processing. Companies are buying disk after disk to support data growth, but five years from now they will run out of space and have accumulated an abundance of disks. This process is costly and unsustainable, increases security risks, and often costs businesses millions.
Businesses need to take a greener approach to data management to reduce storage needs, generate energy savings, and help meet internal and external sustainability goals.
Adrian Knapp is the CEO and Founder of Aparavi
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