Searchable stored data can change how every data center operates.
Every data center in the world has massive amounts of data that is compressed to fit in the space available. The problem is, compressed data is generally not searchable and accessible – it needs to be decompressed first, a process that can take days in searching for a decompressing stored data. AtomBeam Compaction can change that game in every data center in the world.
I’m Charles Yeomans, the CEO of AtomBeam, and I’m thrilled to have been a part of this insightful Fireside Chat alongside our esteemed Chief Scientific Officer, Joshua Cooper, PhD. In this discussion, we delved deep into the problem of accessing stored data, one of the most important issues facing major company CIOs all over the world. Stored data is compressed, and compressed data is not searchable or accessible. Compacted data, unlike compressed data found in every data center, is searchable and randomly accessible. Big companies spend millions and devote a lot of internal resources trying to mine their “data lakes” – huge amounts of data from machines and other sources that have the potential to provide tremendous value to their organizations, but which are very hard to access.
Here’s a common scenario…
Imagine you’re an IoT data analyst for a heavy equipment company, and your boss presents you with the challenging, yet routine problem of determining why a part in a line of the company’s dump trucks is failing more often than it should. Your task is to dig deep into an enormous pool of data stored in your company’s servers to find data messages sent by a sensor monitoring that part, and do analysis on the data to see why this is happening. The problem, once you have the data, is straightforward; you can run various analytical models you have on it and the answer to your boss’ question may present itself. The problem is finding the data you seek.
A reasonable sample of data, you determine, is to look at a sample of sensor readings over five years for 5,000 of the dump trucks in question. Each dump truck has 200 sensors, and each sensor generates 100,000 messages per day. Moreover, the 5,000 dump trucks are a small part of the company’s fleet of machines, which total over 1,400,000. That means the fleet generates 50 quadrillion messages per day, a staggering amount of data. Multiply that 50 quadrillion times five years of data from the fleet, all of it scattered around the company’s data lake. Your work is cut out for you just to find and retrieve the data you need, because the data is all compressed, and you can’t search compressed data. Consequently, it routinely takes days to simply find the data you need to conduct the analysis. On average, data scientists spend around 80% of their time on preparing and managing data for analysis. Crazy, but that is how things really work.
COMPACTION IS A WHOLE NEW APPROACH…
AtomBeam marks the beginning of a paradigm shift.
AtomBeam’s game-changing concept of Codebooks for data reduction is the key to unlocking the power of compacted data. With the right Codebook, compacted data becomes readable by computers. To a computer equipped with a Codebook to decode – nearly instantly – stored, compacted data becomes as searchable and accessible as the data in its original form. Think of it as though you were holding a magnifying glass to scan tiny, otherwise unreadable print to find some particular information in it; except, for a computer, you can perform this scan nearly instantly. Think of the incredible power of that ability compared to the current, antiquated process in use today.
The era of struggling through labyrinthine data piles is over!
AtomBeam’s ingenious solution stands ready to liberate data analysts from endless searches and tedious decompressions. Are you curious to dive deeper into this historic advancement? Unveil AtomBeam’s extraordinary capabilities and learn how it’s poised to redefine the landscape of data technology.
Join us on this journey as we discover what the future of data holds with AtomBeam.
Learn more on https://atombeamtech.com/
