The Stacked Data Podcast

In this episode of Stacked Data Podcast, I’m joined by Manou, Head of Data & X at Medik8, to dive into the unique challenges of leading a small data team—and more importantly, how to overcome them.✅ How do you prioritize when resources are tight?✅ How can small data teams drive real business impact?✅ What strategies help in building a strong team culture?Manou shares practical strategies on ensuring data teams stay focused on high-value projects, align with business goals, and maximize their potential—even with limited resources.If you’re leading (or part of) a small data team, this one’s for you.

🚀 𝐖𝐡𝐲 𝐭𝐡𝐞 𝐒𝐞𝐦𝐚𝐧𝐭𝐢𝐜 𝐋𝐚𝐲𝐞𝐫 𝐢𝐬 𝐭𝐡𝐞 𝐌𝐢𝐬𝐬𝐢𝐧𝐠 𝐏𝐢𝐞𝐜𝐞 𝐢𝐧 𝐃𝐚𝐭𝐚 & 𝐀𝐈 🎙️ Data teams are investing more than ever in AI and analytics, yet many still struggle to make their data truly accessible, consistent, and reliable. One major reason? The semantic layer. Without a curated Semantic Layer, self-serve AI is a pipedream! In the latest episode of the Stacked Data Podcast, I sit down with Sarah Levy, CEO of Euno, to unpack why the semantic layer is often overlooked—and why it’s so crucial for businesses looking to scale AI and analytics effectively. 𝕎𝕖 𝕕𝕚𝕧𝕖 𝕚𝕟𝕥𝕠: 🔹Why so many companies struggle with data consistency and accessibility 🔹What a semantic layer actually is and why it’s a game-changer 🔹How it bridges the gap between raw data and real business impact 🔹The challenges of adoption & why many data teams still don’t have one 🔹How Euno is tackling this problem head-on If you’re working in data and your organisation is pushing for AI, this is a must-listen.

In this engaging discussion, Matt Raninski, Head of Data at Paired, shares his expertise in product analytics and event tracking. He dives into what makes event tracking essential for understanding user behavior and driving product success. Matt offers tips on prioritizing the right data to track, avoiding the pitfalls of over-tracking, and the importance of thorough documentation. He also emphasizes effective communication with non-technical teams and practical strategies for setting up event tracking in mobile apps, making data actionable for growth.

In today's fast-moving, data-driven world, embedding analytics from the start... rather than as an afterthought, is becoming essential. But what does it really mean to design analytics into the DNA of a business process?Have you ever had a stakholder launch a new product and then come to see you as a data team to see how its performing and what the key metrics are? I bet you have, Analytics by design is the process of ensuring data team is at the table from day one to drive the best practices and understand the right metricsIn the latest episode of the Stacked Data Podcast, I sit down with @Barbora Spacilova, Product Data & Insight Manager at @NMI, to dive into Analytics by Design—why it matters, how to implement it, and the challenges that come with it.🔥 𝚆̲𝚎̲ ̲𝚌̲𝚘̲𝚟̲𝚎̲𝚛̲:̲✅ Why ‘Analytics by Design’ is a game-changer for modern businesses✅ How to align data strategy with business goals from day one✅ Real-world examples of companies doing this right✅ The biggest pitfalls to avoid & how to measure successIf you're in data, product, or analytics, this one's for you! 🎧

Join John Azzopardi, Senior Analytics Engineering Manager at Monzo, as he shares insights from his six-year journey in one of the UK's premier data teams. Discover how Monzo scaled its analytics engineering team from 20 to 170 members and the pivotal role of incremental modeling in managing vast data volumes. John discusses the balance of autonomy and direction in projects, key challenges in recruiting, and the future landscape of analytics engineering in fintech. Get ready for a deep dive into innovative data practices!

Karen Francis, a Data Product Manager at B&Q and host of the Women in Data podcast, and Rihanna Kelly, Head of Data at Zeps, dive into the transformational role of Data Product Managers. They share personal stories about their careers in data and discuss the challenges teams face in showcasing their value. Emphasizing the need for better communication and strategic partnership, they highlight how Data Product Managers can bridge gaps between analytics and engineering to drive efficiency and align data initiatives with business objectives.

Is AI coming for data jobs?Gaurav Tiwari, an Engineering Manager at Spotify, joining me on The Stacked Data Podcast. I first encountered Gaurav's insightful perspectives on AI at The London Analytics Engineering Meet-up, I had to get him on the show!With a deep-seated passion for AI, Gaurav brings a critical eye to this rapidly evolving field. We dived deep into the implications of Generative AI on the data landscape and how it will impact your roles and responsibilities in data...Gaurav, shares his thoughts on how AI will impact the life of a data professional…In this episode, we cover:✅ Understanding Generative AI✅ GenAI at the Consumption Layer: Discussing how GenAI is reshaping the interaction between businesses and data through analytics.✅ Benefits of GenAI in Analytics: Exploring the potential benefits GenAI could bring to self-serve analytics platforms.✅ Challenges and Solutions: Identifying the biggest challenges when integrating GenAI into analytics processes and how to address them effectively.✅ Strategic Investment and Pitfalls: Guidance for organisations on where to start their investments in GenAI and potential pitfalls to avoid.✅ Data Engineering AI Impact:✅ Challenges Specific to Data Engineering: Examining the unique challenges data engineers face when integrating GenAI and how to overcome them.✅ Optimal Strategies for Implementation: Recommended strategies for adopting GenAI within data engineering teams and aligning methodologies with new tools.✅ Tools and Technologies: Highlighting specific tools or technologies such as Infer, TurinTech AI and moreGaurav's insights and expertise make this episode a must-listen for anyone interested in the evolving landscape of Generative AI and its impact on data analytics and engineering.

The Semantic Layer, what cand it do?The modern data stack has transformed the way businesses store, prepare, and consume data. Yet, amidst this data revolution, organisations are continuing to encounter challenges such as data quality, inconsistency, and escalating costs. One solution gaining traction is the semantic layer.Excited to announce the latest episode of the Stacked Data Podcast, featuring David Jayatillake, the VP of AI at Cube! We explore the transformative impact of the modern data stack and delve into the intricacies of the semantic layer.David reminisces about being a human semantic layer, translating business logic into usable data in his early career, to setting up an LLM NLP start-up, David has an incredible story and the best insights.In this episode, we cover: David's      journey in the Data & AI space Understanding      the term "semantic layer" and its function within a data      infrastructure The      importance of the semantic layer in the modern data stack Specific      challenges like data inconsistency and scalability that the semantic layer      can effectively address Tangible      benefits of implementing a semantic layer, including enhanced security and      AI capabilities Cube’s      unique approach to the semantic layer and the value it brings to organisations Exciting      developments and future plans for Cube in the evolving data landscapeDavid's insights and expertise make this episode a must-listen for anyone interested in the modern data stack and the role of the semantic layer. Don't miss out on this deep dive into one of the most critical components of data infrastructure!

Data strategist Dylan Anderson from Rekite emphasizes the importance of a holistic view of the data ecosystem. Topics include navigating data roles, avoiding siloes, consequences of poor communication, and the benefits of a broad understanding. The podcast explores challenges in understanding interconnected data elements, the significance of data unicorns, stakeholder management, treating data as a product, and the importance of empathy in the data field.

Data Contracts have gained a huge amount of traction over recent years as Data teams strive to increase the quality of their offering.This week on Stacked Data podcast I had the pleasure of taking a deep dive into the world of data contracts with none other than Andrew Jones, the Principal Engineer at GoCardless and the pioneer behind this transformative concept.If you haven’t heard of Data Contracts they bring several significant benefits to a data team and their data management practices, including:Improved Data QualityStandardisation and ConsistencyScalabilityData GovernanceFacilitates Data Monetization🔍 Episode Highlights: Introduction      to Data Contracts: Andrew kicks off our episode with a basic      understanding of what data contracts are and how they revolutionise GoCardless      approach to data management. Why      Data Contracts?: Discover the crucial role data contracts play in      today's complex data landscape and why Andrew felt compelled to develop      them. Benefits      Unveiled: Learn about the substantial advantages data contracts bring      to data governance, integrity, and management practices. Real-World      Impact: Andrew shares compelling examples from his experiences at      GoCardless, illustrating the significant improvements data contracts have      facilitated. Addressing      Common Data Challenges: Find out how data contracts can solve      prevalent issues like data inconsistency and quality concerns. Implementation      Insights: Gain practical strategies and tips for integrating data      contracts into your data management processes, alongside the best tools      and cultural shifts required for success. Overcoming      Obstacles: Hear about the common challenges organizations face when      adopting data contracts and the solutions to overcome them. Future      Perspectives: What does the future hold for data contracts? Andrew      shares his vision for adapting to upcoming data management trends and      opportunities. Final      Thoughts: Before we wrap up, Andrew imparts some invaluable advice for      anyone considering data contracts as part of their data strategy.Andrew Book: Driving Data Quality with Data Contracts: A comprehensive guide to building reliable, trusted, and effective data platforms: Amazon.co.uk: Jones, Andrew: 9781837635009: Books