โฌ๏ธ Data volumes continue to rise. In fact, within industries like #engineering and #finance, the volume and volatility of log data have even outpaced the capacity of traditional #SIEM and analytics tools. ๐ฐ What this means is... with orgs facing high costs and fatigue, the ones that thrive will be the ones that treat storage and retrieval as distinct functions. ๐ค
This is where selective retrieval comes inโthe ability to triage, park, and later selectively ingest high-volume data from a centralized repository for forensic or compliance-driven investigation. ๐
Read this excellent article by #Graylog's Adam Abernethy in BigDATAwire to learn about:
๐ Selective retrieval examples in the real world
โ ๏ธ Risk coverage without always-on cost
๐ Flexibility without architectural lock-in
๐ป The technological shifts that are converging to make selective retrieval possible and necessary
โ๏ธ How selective retrieval bridges the gap between data engineering complexity and #security usability
๐ผ The business case for selective retrieval, especially for mid-size IT teams
๐ Regaining control over data sprawl
โ More
https://www.bigdatawire.com/2025/07/14/rethinking-risk-the-role-of-selective-retrieval-in-data-lake-strategies/ #datalake #logdata #datamanagement @bigabe @bigdatawirenews




