Petabyte-Scale Analytics: Big Data Challenges and Solutions

If you Google the phrase “big data,” you will probably get a big data overload of articles, research, surveys, and predictions about the subject. There is no need to explain again what “big data” is, why it is critical for any business which desires to succeed, and that its growth continues, driven by people, machines, and corporations. In 2021 alone, Forrester estimated that insights-driven businesses would generate $1.8 trillion.

But when someone says, “big data,” how much data do you think that is? In the past, we used to think that petabyte (1,123.899,906,842,624 bytes) databases were solely the problem of huge enterprises or governments, but according to IDC and Seagate, the average enterprise data volume grows by 42.2% annually. Meaning, today’s peta-scale companies are tomorrow’s average.

So, how big exactly is a petabyte? To put this into perspective, here’s BLASTERTECHNOLOGY’s perfect  illustration:

It is important to note that not every enterprise that stores petabytes of data sees business value in historically analyzing this amount of data. Therefore, let’s define membership in the Peta-club as a company that generates or processes over 1 Petabyte of data on a daily basis.

Although analyzing and processing petabytes of data seems like the near-future challenge of most companies, some are already dealing with it on a daily basis. This might bring to mind tech giants (MAMAA – Meta, Alphabet, Microsoft, Amazon, Apple), but believe it or not, even an average factory running predictive maintenance on its production floor or a smart city easily reaches Petabyte-club status. Media and retail giants such as Netflix and Walmart are also part of this club, but the definite current leader is the Large Hadron Collider at CERN, where particle collisions create 1PB of data per second.