β¬οΈ 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. π° 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. π€
This is where selective retrieval comes inβthe ability to triage, park, and later selectively ingest high-volume data from a centralized repository for forensic or compliance-driven investigation. π
Read this excellent article by #Graylog's Adam Abernethy in BigDATAwire to learn about:
π Selective retrieval examples in the real world
β οΈ Risk coverage without always-on cost
π Flexibility without architectural lock-in
π» The technological shifts that are converging to make selective retrieval possible and necessary
βοΈ How selective retrieval bridges the gap between data engineering complexity and #security usability
πΌ The business case for selective retrieval, especially for mid-size IT teams
π Regaining control over data sprawl
β More
https://www.bigdatawire.com/2025/07/14/rethinking-risk-the-role-of-selective-retrieval-in-data-lake-strategies/ #datalake #logdata #datamanagement @bigabe @bigdatawirenews





