The value of data has grown tremendously over the years. You’ve probably heard the claim that data is “the new oil”, but organisations are collecting and storing as much data as they possibly can without knowing what to do with the data effectively. So in the blind race to become data-driven businesses, organisations have amassed massive data lakes which are turning into resource-hogging data swamps.
Also, the rate at which data is being created is much faster than ever before. With advancements in technology, digital transformation, and the continued development of the Internet of Things (IoT), more and more users, devices and things are coming online. Unfortunately, part of the problem is that the solutions brought forth by the rise of big data several years ago can no longer address today’s requirements because the fundamental principles around data itself have changed.
Data comes in all shapes, forms and sizes, especially with more streaming data coming in from non-traditional smart things and the IoT. It can be big or small, structured or unstructured, machine or human. The scale and complexity of this new challenge go beyond big data. We are at the dawn of the extreme data era.
In the age of extreme data, businesses need to move beyond being informed or validated by data to being powered by data. In this new world, it’s all about using agility to help drive competitive advantage, to deliver services and offerings out to customers before the competitors. Companies, no matter how big or powerful they may seem now, that fail to keep up will be overtaken, left behind and forgotten.
Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, said it best when he said, “In the new world, it’s not the big fish which eats the small fish. It’s the fast fish which eats the slow fish.”
While the big data world was more geared towards structured batch processing, we now live in a world that requires instant analysis of all different kinds of data. We need to not only ingest complex, unpredictable data, but also process it as it’s hitting the system and make sense of it in real-time in order to drive real value for the business.
To gain critical insight, organisations need to leverage accelerated analytics, data visualisation, and machine learning. They need to run complex queries on massive amounts of extreme data, but this is difficult, slow, and sometimes impossible with traditional databases. New solutions are emerging. The rise of accelerated parallel computing powered by GPUs has created a new processing paradigm that can manage massive volumes of data. Innovative companies are building GPU-powered engines that can take streaming data and translate it into insight instantaneously.
At the end of the day, effectively using data in real-time is the essential ingredient that separates the winners from the losers in this post-big data world. Knowing this, Kinetica and Dell EMC have teamed up to help businesses tackle the challenges of the extreme data economy. They have combined their expertise to offer a highly complementary solution that combines Kinetica’s GPU-accelerated engine for analytics, location-based visualisation, and machine learning with Dell EMC’s high-density compute servers in a single package.
To learn how Dell EMC and Kinetica are powering the extreme data economy, click here.