Data

Explore the nine building blocks that make up the Data Product Canvas. Learn how to approach each component to design data products that deliver real value and avoid common pitfalls.

Turn data initiatives into business success stories with the Data Product Canvas. This practical framework helps teams design data products that deliver real value, avoid common pitfalls, and align with business objectives.

AI agents dominated Big Data LDN 2025, but the real story wasn't the technology, it was which organisations could actually deploy it successfully. After five years tracking industry evolution through this event, one pattern emerged clearly: the winners had built their foundations first. For CTOs making platform decisions now, the strategic imperative isn't choosing between innovation and governance; it's recognizing that governance enables innovation at scale.

FabCon is a conference dedicated to everything Microsoft Fabric. Day 3's sessions included migration, Databricks, Spark optimisation, and more.

FabCon is a conference dedicated to everything Microsoft Fabric. Day 2 featured deep dives into OneLake, Maps in Fabric, and multi-agent AI systems.

FabCon is a conference dedicated to everything Microsoft Fabric. Day 1 was mostly focused around the hundreds of new feature announcements.

The Medallion Architecture consists of three data tiers: Bronze (raw), Silver (clean), and Gold (projected). Data moves through these three tiers and becomes more opinionated at each stage.

Understand why label encoding is the preferred technique for encoding categorical data for analysis in Power BI over one-hot encoding.

One-hot encoding and label encoding are two methods used to encode categorical data. Understand the specific advantages and disadvantages of these techniques.

Fix the following issues: Errors converting large datasets to pandas, pandas for Spark is very slow, and pandas for Spark column reduction doesn't reduce data.

Spark doesn't always interpret JSON how we'd like. For example, if each key/value pair in a JSON object is conceptually one item, Spark won't give you a row per item by default. This article shows how to nudge Spark in the right direction.