![]() It’s now possible to take advantage of millions or billions of individual pieces of data, and have systems identify patterns, sources of value, areas of opportunity and risk that simply weren’t possible before. These huge advances in data analysis and machine learning makes data more valuable over time.įor enterprises, this has placed tremendous strain on their applications, and on the storage those applications depend on. Scrambling to adapt to the new landscape of possibilities, businesses are forced into a “better to keep it than miss it later” philosophy when it comes to their data. Longer data life spansĪt the same time, the advent of machine learning has enabled entirely new sources of value for businesses and their customers. Higher resolution causes file sizes to grow more than linearly – a doubling of the resolution of a digital photograph, for example, increases its size by four times.Īs the world demands more fidelity from digital assets, its storage requirements grow. ![]() The resolution of digital sensors and scientific equipment is also constantly increasing. This level of fidelity for truly immersive viewing experiences was unthinkable just a few years ago. Technical advances in hardware and software systems are enabling new capabilities for businesses of all kinds.įor example, media and entertainment companies are now able to standardize around uncompressed 4K video, with 8K on the horizon. It’s not an exaggeration to say that the greatest assets for these organizations are the file-based seismic data used for natural gas and oil discovery. For example, large machine-generated data sets in life sciences are making groundbreaking discoveries and life-saving medical treatments available. Because of its tremendous value to researchers, healthcare providers, and patients, the need for such data will only grow.Īs another example, oil and gas companies are using data to create tremendous value for their customers. The Internet of Things (IoT) is powering a transformation in the value of data for enterprises of all kinds, spanning all data-intensive industries.ĭata is powering value and growth as never before. Successful companies increasingly rely on machine-generated data for core business operations and insight. Longer data lifespans, and trends toward globalization that create distributed computing and storage resources.The ever-increasing resolution and fidelity of these digital assets, and.The prevalence of video as a data type across all industries.The vast increase in machine-generated data.There are four trends contributing to the amount of data companies must store: ![]() This is ten times the data generated in 2016.Īpproximately 90 percent of this growth will be for file and object storage. IDC predicts that the amount of data created will reach 40 zettabytes (a zettabyte is a billion terabytes) by 2020, and that there will be more than 163 zettabytes by 2025. There’s also no limit on file size at the extremes-small and large, and no limit on availability, whether on-premise, in the cloud or in geographically distributed data centers. ![]() In today’s world of abundant data, there’s no limit on the number of files – billions or trillions of files aren’t just possible, but are becoming commonplace. Yet, these assets remain at the core of the business, and file-based workflows are the crucial pipelines for those assets. This data is produced and consumed by file-based applications and systems which make up the foundation of modern digital production pipelines. This means that companies are now generating significantly more file-based data than ever before.Īs a result, businesses are fast outgrowing their legacy file systems, and can no longer manage their massive collections of digital assets. This is the era of unprecedented data scale. Over the past five years, we have seen a dramatic reduction in the economics of data creation, and an equally dramatic reduction in the cost of data storage. We’ve evolved from the era of “ How do I store data?” to “ How do I intelligently and efficiently manage data?” Plus we’re in an era where billions of files – or more – are the norm. While organizations have historically relied on data to drive business, that data was often expensive to acquire and store. The fundamental nature of how companies use computing to drive innovation, agility, and responsiveness has changed significantly over the past five years. ![]()
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