Anti-money laundering (AML) is not a singular workload. It is seven data jobs wearing one regulatory label, and almost nobody building or buying AML technology treats them separately. If you work in financial services infrastructure, you’ve likely seen “AML” on a requirements document, a vendor slide, or a budget line. Compliance officers quote regulation at
Demystifying Anti-Money Laundering Read More »
Recently I have had the impression that a new data architecture is forming. My instinct says that is wrong, because we already have more architectures than most organisations know what to do with, and adding another one to the pile is nobody’s idea of progress. But the signals keep arriving: Machine-generated data has stopped being
Demystifying Why Data Architectures Change Read More »
Last year I gave an agent read access to a warehouse, a schema catalogue, and a brief to explain movements in a set of business-critical numbers. It produced an invoice I had not anticipated. Accuracy was never the difficulty; the model was largely correct. What consumed the budget was interrogation. Before it could attempt anything
The Economics of Agentic AI Analytics Read More »
Most database shops have a caching layer. Redis, Memcached, something custom. Reads hit the cache, misses hit the database, and someone owns the invalidation logic, the TTLs, and the 2 AM incident when the cache goes stale. Oracle 26ai introduces True Cache, and it works nothing like Redis. It’s a diskless, read-only database replica that
True Cache on Oracle 26ai Read More »
In the AI data infrastructure race, Oracle wants you to run AI inside your database. Not call an API. Not ship your data to an external LLM company. Not stand up a separate vector database. Run the whole thing on-prem, behind your firewall, managed by your data team. That’s what the Private AI Services Container
Running Oracle’s Private AI Stack On-Premises Read More »
Everyone is talking about AI. AI this, vector that, vector indexes eating your storage, running out of memory. I deployed 26ai on my lab cluster and went through the internals so you don’t have to guess what’s actually going on under the hood. Brace yourself for this DDL and DML ride. Here’s the short version
Oracle 26ai Vector Search Internals Read More »
Oracle 26ai came out. I deployed it, went to run my RMAN workflows, and immediately noticed things had changed. After an hour of reading through the 26ai Backup and Recovery documentation and testing against a live instance I found enough worth writing down. This post is part change log, part lab journal for what’s different
What Changed in RMAN for Oracle 26ai Read More »
Oracle 26ai can join external tables backed by S3 Parquet files with regular internal tables in a single SQL statement, without data movement, ETL pipelines, or Spark. The optimizer treats S3-backed external tables as another data source and picks the right join strategy automatically. This post shows how to build a customer dimension table from
Hybrid Analytics with Oracle 26ai and S3 Data Read More »
