AI Data Platform Series: Gold Layer Vehicle Movements

This is the seventh post in the AI Data Platform series. The previous post built tfl.gold.arrivals_board, a live view of the next buses at every stop, and connected it to Oracle Analytics Cloud. What it couldn't do was say where anything is: TfL's arrivals feed carries stop IDs and names, but no coordinates. This post adds them. First a reference table with the location of every stop on every bus line, then an estimate of where each bus on line 25 actually is right now, drawn along the real road it drives on.

Read more

AI Data Platform AI Data Platform Series AIDP Data Engineering Geospatial Maps Medallion Architecture OAC Oracle Analytics Posts Real-Time Data Pipelines Spark Structured Streaming

AI Data Platform Series: OAC MCP Server and Streaming Data

This is the eighth post in the AI Data Platform series. Over the last two posts, the gold layer grew three live pieces: an arrivals board for every bus stop in London, a stations reference table, and estimated positions for every bus on line 25, all queryable from Oracle Analytics Cloud. Until now, every question I asked that data was either SQL in a notebook or a workbook in OAC. This time I connected Claude to OAC through Oracle Analytics' MCP server and simply asked, in plain language, what was going on.

Read more

AI Data Platform AI Data Platform Series AIDP Claude Generative AI Logical SQL MCP Model Context Protocol Natural Language Querying OAC Oracle Analytics Posts

AI Data Platform Series: Gold Layer Arrivals Board

This is the sixth post in the AI Data Platform series, following Just Streams: Real-Time Data Pipelines on OCI (the series intro), Setting Up the AI Data Platform Environment (stage 0), OCI Streaming and the Stream Producer (stage 1), Bronze Layer: Spark Structured Streaming (stage 2), Silver Layer: Spark Structured Streaming (stage 3), and the Comparing Bronze and Silver with DBeaver detour. Silver gave me one clean, always-current row per bus, stop, line and direction. This post covers the first half of stage 4: turning that into a live arrivals board, the kind you see on a screen at a bus stop, and putting it in front of Oracle Analytics Cloud.

Read more

AI Data Platform AIDP Data Engineering Delta Lake Maps Medallion Architecture OAC OCI Oracle Analytics Posts Real-Time Data Pipelines Spark SQL

Why BI and DWH Are Not Just an IT Project, but a Business Investment

Most BI conversations start with a dashboard and end with a budget line. That's backwards. The tool you click on is only the last step in a chain — underneath it sits a data warehouse doing the unglamorous work of cleaning, reconciling, and remembering your data so the numbers on screen can actually be trusted. Treat BI as a software purchase and you'll get pretty charts nobody fully believes. Treat it as a business investment — dashboard and foundation together — and you get something people make decisions with.

Read more

Business Intelligence data governance Data Quality Data Strategy Data Warehouse Hero Posts

AI Data Platform Series: bronze vs. silver

This is a short detour in the AI Data Platform series, sitting between "Silver Layer: Spark Structured Streaming" (stage 3, link to be added once that post is live) and the upcoming gold layer post. Every table in this series so far has only ever been queried from inside an AIDP Workbench notebook. This time I wanted to connect a plain SQL client, DBeaver, straight to the cluster over JDBC, and use it to look at bronze and silver side by side: same underlying event, two very different shapes. Along the way, DBeaver's own table-metadata commands surfaced something I'd walked past without really registering back in the bronze post: both tables are already readable as Apache Iceberg tables, no extra work required.

Read more

AI Data Platform Series Apache Iceberg DBeaver Delta Lake JDBC oracle cloud infrastructure Posts Spark Structured Streaming

AI Data Platform Series: Silver Layer Spark Structure Streaming

This is the fifth post in the AI Data Platform series, following Just Streams: Real-Time Data Pipelines on OCI (the series intro), Setting Up the AI Data Platform Environment (stage 0), OCI Streaming and the Stream Producer (stage 1), and Bronze Layer: Spark Structured Streaming (stage 2). That last post landed every arrival prediction as-is into an append-only Delta table, tfl.bronze.arrivals_bronze. This post covers stage 3: cleaning that data up, keeping only the latest prediction per vehicle/stop/line/direction, and upserting it into a proper silver table.

Read more

AI Data Platform Series: Bronze Layer Spark Structured Streaming

This is the fourth post in the AI Data Platform series, following Just Streams: Real-Time Data Pipelines on OCI (the series intro), Setting Up the AI Data Platform Environment (stage 0), and OCI Streaming and the Stream Producer (stage 1). That last post got live TfL bus-arrival predictions flowing into the tfl-arrivals OCI Streaming topic. This post covers stage 2: a Spark Structured Streaming job that reads the topic, parses it, and lands it as an append-only Delta table, the bronze layer.

Read more

AI Data Platform AIDP Data Engineering Delta Lake Kafka OCI Streaming OCI Vault Posts Python Spark Structured Streaming

AI Data Platform Series: OCI Streaming and Stream Producer

This is the first technical post in the series that opened with Just Streams: Real-Time Data Pipelines on OCI. That post walked through the whole TfL-bus-arrivals demo Sandi Holub and I gave at Make IT 2026 and UKOUG 2025. This one goes one layer down: the piece that gets live data into the platform in the first place — a small Python producer and an OCI Streaming topic.

Read more

AI Data Platform AIDP Data Engineering Kafka OCI Compute OCI Streaming Posts Python Real-Time Data Pipelines

My Presentation @ Oracle Technology Roundtable, August 2026

On 26 August 2026 in Ljubljana, I took part in the Oracle Technology Roundtable, where I presented together with my SmartQ colleagues Mojca Gros and Grega Dvoršak.

For the event, we prepared a joint presentation titled “Oracle Analytics & AI”, with the subtitle “Oracle Private Agent Factory in Oracle Analytics Server.” The session brought together three closely related topics: the latest Oracle Analytics Server platform, the use of Model Context Protocol with OAS, and Oracle AI Database Private Agent Factory.

Read more

Agent Builder AI Agents Events MCP OPAF Oracle Analytics Server Oracle Database 26ai

AI Data Platform Series

This is the overview of my AI Data Platform series. It follows one real-time demo from start to finish: live London bus arrival predictions from Transport for London (TfL), streamed through OCI into Oracle AI Data Platform (AIDP), refined through a bronze, silver and gold medallion architecture, and finally analysed in Oracle Analytics Cloud, including in plain language through the Oracle Analytics MCP Server.

Read more

AI Data Platform AIDP OCI Series

AI Data Platform Series: Setting Up the AI Data Platform Environment

This post backs up a step from the rest of the AI Data Platform series. Before any bronze/silver/gold Spark job can run, or a stream producer can hand data off to something downstream, the AI Data Platform (AIDP) environment itself has to exist: a Workbench, a workspace, a catalog, compute, and a place to keep secrets. This post walks through building all of that from nothing on a brand-new OCI tenancy, using the same TfL bus-arrivals demo's naming (catalog tfl, schemas bronze/silver/gold) as the throughline.

Read more

AI Data Platform AIDP OCI Posts

Connecting OPAF Chat to Oracle Analytics Cloud via MCP

This post explores how to connect Oracle AI Database Private Agent Factory (OPAF) with Oracle Analytics Cloud (OAC) using the Model Context Protocol (MCP). It walks through the OAuth configuration, MCP server setup, and Agent Builder flow needed to let a private OPAF agent query live, governed OAC subject areas. The result is an analytics-aware AI assistant that can discover metadata, generate Logical SQL, and answer questions using trusted enterprise data—without duplicating the semantic model or underlying data.

Read more

Agent Builder AI Agents Logical SQL MCP Model Context Protocol OAC OCI OPAF oracle analytics cloud Oracle Private Agent Factory Posts