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Stacked Data Podcast

Podcast Stacked Data Podcast
Cognify
It has become evident to me that many data teams are grappling with similar challenges. Learning from the experiences of others can be incredibly valuable, whic...

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5 of 27
  • 027 - Analytics by Design – Building Data-Driven Products from Day One
    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! 🎧
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  • 026 - How Monzo hyper-scales Analytics Engineering
    We’re back, and we’re kicking off with a BANG! 💥Monzo is home to one of the most respected data teams in the UK—true trailblazers in Analytics Engineering, regularly sharing insights into how they scale data. This episode is no different!I had the pleasure of sitting down with John Azzopardi, Senior Analytics Engineering Manager at Monzo, who’s been with the company for over 6 years. We dive deep into how Monzo’s data team scaled from 20 to over 170 people and how Analytics Engineering plays a crucial role in supporting their hyper-growth.In this episode, we cover: ✅The evolution of the Analytics Engineering function at Monzo ✅How the team is structured for success and their key responsibilities ✅Challenges of scaling Monzo’s data warehouse and infrastructure ✅Why incremental modeling is a cornerstone of their data strategy ✅The future of Analytics Engineering in fintech and what’s next for MonzoIf you’re looking to learn from one of the UK’s top data teams, this episode is a must-listen! 🎧✨ Hear firsthand how Monzo is mastering data at scale and driving innovation in their infrastructure.We’re dropping new episodes every other week, so make sure to FOLLOW & SHARE to stay in the loop!#Podcast #Fintech #AnalyticsEngineering #DataEngineering #Monzo #Data #Innovation #DataInfrastructure #Scaling #IncrementalModeling #TechLeadership #ModernData
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  • 025 - The Rise of the Data Product Manager…
    The Rise of the Data Product Manager…How often have you joined a data team where data is poorly understood by the business, siloed, and churning out tickets with little impact? Or found that the Analytics team doesn’t communicate with Data Engineering, leading to project delays due to missing data?These common challenges underscore the need for a new role that’s gaining traction: the Data Product Manager. This week on The Stacked Data, I'm joined by Karen Francis, a Data Product Manager at B&Q, and Rianna Kelly a Head of Data at Zeps.Karen and Rianna have firsthand experience with these issues and many more. They’ve seen how powerful and transformative the role of a Data Product Manager can be. In this episode, they share insightful stories and discuss why this role is crucial for high-performing modern data teams.We discuss: The responsibilities of a Data Product Manager The typical challenges they overcome How Data Product Managers drive value and efficiency Case Studies and Success Stories Why more data teams need to adopt this roleTune in to gain valuable insights and understand why the Data Product Manager is essential for any data-driven organization.
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  • 024 - Is AI coming for your job?
    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.
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  • 023 - The Semantic Layer, what can it do?
    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!
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About Stacked Data Podcast

It has become evident to me that many data teams are grappling with similar challenges. Learning from the experiences of others can be incredibly valuable, which is why I am thrilled to announce the launch of The Stacked Podcast. This podcast is dedicated to sharing stories, pain points, challenges, and solutions within the data industry.I will be conducting interviews with industry leaders, delving into their cutting-edge projects, exploring the hurdles they faced, and how they triumphed over them. My ultimate goal is to provide you with insights and advice that will empower your team and propel your career forward.www.cognifysearch.com
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