The Data Radio Show - Bought to you by the Data Innovators Exchange

In the final Data Pro Newsletters of 2025, we reflect on the transformative shifts in data engineering throughout 2025, framing the year’s rapid evolution as a series of foundational changes. The narrative highlights a transition from expensive, centralised AI models toward efficient, local deployment and the rise of autonomous agents capable of deep research and coding. It details how the industry moved past early retrieval methods and "vibe coding" to embrace high-capacity context windows and Large Behaviour Models that interact with the physical world. However, the text warns of a governance crisis, noting that many AI projects fail due to poor data quality and a lack of oversight. Ultimately, the role of the data engineer is redefined as an AI systems architect who must manage real-time data streams and ensure the safety of autonomous actions. These developments suggest that the future of the field relies on rigorous verification and architectural discipline rather than mere hype. Join the Data Innovators Exchange for free at https://www.skool.com/data-management-innovators-4116/about Sign up for the free Data Pro Newsletter at https://www.datapro.news/subscribe

Over the past few months, Ignition from Australia and Nexus Data from South Africa have been teaming up to look at best selling author Zjaen Coetzee's best selling book, Driving RAPPID Results - a look at the frameworks and methodologies within the data industry that can be improved to get better results for everyone.  In this Podcast, Zjaen and Ignition CEO Julien Redmond sit down and discuss the series, what they learnt and what the future has in store. Join the Data Innovators Exchange for free at https://www.skool.com/data-management-innovators-4116/about Sign up for the free Data Pro Newsletter at https://www.datapro.news/subscribe

In This Issue of the Data pro News, we look at an excerpt from "The Data Engineering Mandate for 2026," outlines the critical transformation facing data engineering professionals as Artificial Intelligence matures and demands robust infrastructure. The author argues that legacy, batch-oriented data systems are insufficient for modern AI, particularly for Retrieval-Augmented Generation (RAG), which requires real-time, low-latency data pipelines. To resolve this, the document proposes five key shifts for 2026, including the widespread adoption of real-time streaming infrastructure (like Change Data Capture), the elevation of data contracts into governance mandates, and the consolidation around lakehouse architectures. Furthermore, it addresses the paradox of AI automating foundational tasks, which necessitates data engineers pivoting to high-level architecture, governance, and AgentOps to manage fragmented AI agent ecosystems. Ultimately, the article asserts that AI success is now bottlenecked by data infrastructure maturity, requiring immediate investment in real-time platforms and automated governance. Join the Data Innovators Exchange for free at https://www.skool.com/data-management-innovators-4116/about Sign up for the free Data Pro Newsletter at https://www.datapro.news/subscribe

This analytical article from the Data Pro News provides a comparative overview of the newly released Gemini 3 Pro and Claude Opus 4.5 large language models, specifically focusing on their utility and risks within the field of data engineering. The author contends that while Gemini 3 offers a revolutionary low cost-to-context ratio and compelling multimodal capabilities (such as converting whiteboard diagrams to code), it presents a significant liability due to an alarming 88% hallucination rate when it should ideally abstain from answering. Conversely, Claude Opus 4.5 is portrayed as the more reliable and semantically robust choice for complex SQL generation and agentic refactoring workflows, despite its higher token cost. Ultimately, the piece advocates for a hybrid "bicameral" architecture, suggesting professionals should orchestrate both models—using Gemini for low-risk bulk processing and context scanning, and reserving Claude for high-stakes logic execution—to achieve robust and economically viable data pipelines. Join the Data Innovators Exchange for free at https://www.skool.com/data-management-innovators-4116/about Sign up for the free Data Pro Newsletter at https://www.datapro.news/subscribe

This episode we're taking a detailed examination of how Artificial Intelligence (AI) is rapidly transforming the retail industry, particularly focusing on the high stakes of the upcoming holiday shopping season as a crucial test for new technology investments. It highlights that major brands like Puma and Levi’s are already integrating AI into business operations and consumer outreach, signalling that those who hesitate risk falling behind the competition. The core benefit of AI is its ability to combat "decision fatigue" by offering hyper-personalised shopping experiences and accelerating product discovery, which is already attracting consumers, with nearly half of shoppers having used AI tools for retail purchases. Furthermore, the text suggests that AI's capacity to deliver speed, relevance, and convenience could potentially shift the balance of apparel sales back toward online channels, challenging the plateauing growth of e-commerce. Ultimately, the success of AI this holiday season—especially in delivering positive, friction-free experiences—will determine whether it moves from a novelty to a necessity, accelerating future retail strategy and investment. Join the Data Innovators Exchange for free at https://www.skool.com/data-management-innovators-4116/about Sign up for the free Data Pro Newsletter at https://www.datapro.news/subscribe