Analyzing the full scope of data at a petabyte scale is very challenging. Most organizations find it too expensive or too slow and wearisome, so they compromise and base their analytics on a fraction of the data.If your organization generates petabyte-scale data, analyzing it in full scope would benefit you in several ways:
- Greater accuracy of the insights gained from analysis, as more data points are taken into account.
- A deeper understanding of patterns and trends that may not be visible in smaller data samples.
- Improved predictive modeling for machine learning (ML) projects, as bigger and more quality datasets can make more accurate predictions.
In this technical whitepaper, we will explain how we implemented the cutting-edge technology of SQreamDB at one of the biggest electronics enterprises in Asia, allowing it to analyze data at a petabyte scale, save tremendous costs on analytics, and increase yield.