SIBYL: A machine learning-based framework for forecasting dynamic workloads
This paper was presented at the ACM SIGMOD/Principles of Database Systems Conference (opens in new tab) (SIGMOD/PODS 2024), the premier forum on large-scale data management and databases.
In today’s fast-paced digital landscape, data analysts are increasingly dependent on analytics dashboards to monitor customer engagement and app performance. However, as data volumes increase, these dashboards can slow down, leading to delays and inefficiencies. One solution is to