Data lineage is a cornerstone of modern data engineering, but as pipelines grow, the cost of storing and querying lineage metadata can quietly explode. In this episode, Lucas and Luna explore how one mid-sized fintech company discovered that their lineage graph had become a bottleneck, driving up compute costs and slowing down impact analysis. They walk through the surprising economics of lineage: the storage overhead, the query complexity, and the hidden operational burden. They also discuss practical strategies for pruning and partitioning lineage data, and why some teams are moving to a hybrid approach that balances granularity with cost. Tune in to learn why your lineage metadata might be your next data cost frontier—and what you can do about it.

#DataLineage #DataCosts #DataEngineering #DataOps #MetadataManagement #DataInfrastructure #CostOptimization #DataPipelines #DataGovernance #Fintech #DataAnalytics #TechBusiness #DataTeams #LineageGraph #DataStorage #QueryPerformance #FexingoBusiness #BusinessPodcast

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On this episode of The Data Business Podcast, Lucas and Luna dive into the world of data clean rooms — secure environments where companies can share and analyze data without exposing raw customer information. They explore how brands like Walmart and Disney are using clean rooms to power ad campaigns and measure performance while respecting privacy regulations. With the death of third-party cookies, clean rooms are becoming essential infrastructure for digital advertising. The hosts break down the technology — from cloud-based solutions to privacy-enhancing computation — and discuss the real business value: better targeting, accurate attribution, and deeper customer insights without the legal headaches. They also examine the challenges: data governance, cost, and the skills gap. If you're in marketing, analytics, or data strategy, this episode offers a clear roadmap for leveraging clean rooms effectively. Tune in to learn how clean rooms are quietly reshaping the data collaboration landscape.

#DataCleanRooms #PrivacySafeAnalytics #DataCollaboration #ThirdPartyCookies #DigitalAdvertising #Walmart #Disney #BusinessPodcast #DataInfrastructure #PrivacyTech #MarketingAnalytics #DataGovernance #CloudComputing #DataStrategy #AdTech #FexingoBusiness #BusinessAndTechnology #DataBusiness

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In this episode of The Data Business Podcast, Lucas and Luna explore the practical impact of open table formats like Apache Iceberg, Delta Lake, and Apache Hudi on data infrastructure costs. They discuss how a mid-sized SaaS company reduced storage and compute costs by 30 percent after migrating to Iceberg, the role of partitioning and compaction in cost optimization, and the trade-offs between the three main formats. They also touch on the emerging trend of open data lakehouses and how these formats enable more efficient querying across engines. With a focus on real-world numbers and decision-making, this episode provides actionable insights for data leaders evaluating their storage and compute strategies. Tune in to understand why open table formats are becoming a standard part of modern data stacks and how they can help your team save money without sacrificing performance.

#OpenTableFormats #ApacheIceberg #DeltaLake #ApacheHudi #DataInfrastructure #DataCostOptimization #Lakehouse #DataEngineering #DataManagement #CloudData #Analytics #TechPodcast #Business #FexingoBusiness #BusinessPodcast #DataPodcast #DataLeaders #DataStrategy

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Feature stores are quietly becoming the backbone of real-time machine learning, but most data teams still treat them as just another database. In this episode, Lucas and Luna dig into what a feature store actually is, how it differs from a traditional feature pipeline, and why the ones that succeed are the ones that treat features as versioned, governed products — not just cached values. They walk through a concrete example from a large European e-commerce company that cut its real-time inference latency from 400 milliseconds to 40 milliseconds by moving feature computation online, and they talk about the hard part: keeping training and serving features consistent. Along the way, they touch on the rise of the 'online-offline consistency' problem, the tension between data engineering and ML engineering over who owns the feature store, and why some teams are now using feature stores as a form of data contract for their models. If you're building real-time ML, this episode gives you a clear mental model for when a feature store is worth the operational overhead — and when it's just another layer of complexity.

#FeatureStore #RealTimeML #MachineLearning #DataEngineering #MLOps #DataProducts #DataGovernance #OnlineInference #OfflineTraining #DataContracts #DataInfrastructure #DataScience #StreamingData #DataPipelines #BusinessAndTechnology #TechPodcast #FexingoBusiness #BusinessPodcast

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On this episode of The Data Business Podcast, Lucas and Luna explore how data teams are turning to DataOps—a set of practices borrowed from DevOps—to cut down on wasted effort, reduce errors, and speed up delivery. They dig into the real story of a mid-sized e-commerce company that cut its data pipeline failure rate by 70 percent in six months by adopting DataOps principles: version control for code, automated testing, and continuous integration for data pipelines. The hosts discuss why DataOps has become a must-have in 2026, how it changes the role of data engineers and analysts, and the cultural shifts that make it work. They also get practical: what to automate first, how to measure success, and where the common pitfalls lie. If you're building or running a data team and want to move faster without breaking things, this episode gives you a clear playbook.

#DataOps #DataEngineering #DataPipelines #DevOpsForData #DataQuality #DataAutomation #DataCulture #DataStrategy #BusinessAndTechnology #FexingoBusiness #BusinessPodcast #DataManagement #AnalyticsEngineering #DataInfrastructure #CIForData #DataVersioning #DataTeam #DataLeadership

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In this episode of The Data Business Podcast, Lucas and Luna explore how modern data teams are leveraging lakehouse architectures to slash storage and compute costs while improving query performance. They examine a real-world case of a streaming service that cut its data infrastructure bill by 30% by migrating from a traditional data warehouse to a lakehouse setup, and discuss the trade-offs involved in terms of governance, schema enforcement, and team skill sets. The hosts break down the key components — from open table formats like Delta Lake and Apache Iceberg to the role of caching and partitioning — and offer practical advice for listeners considering a similar migration. They also touch on the growing trend of 'data cost per query' as a metric for optimizing spend, a topic previously covered in episode 149, and look ahead to how lakehouse architectures might evolve with the rise of AI-driven data workloads. If you're a data engineer, analyst, or business leader trying to balance performance and cost, this episode gives you a clear framework for thinking about your data stack.

#Lakehouse #DataArchitecture #DataCostOptimization #DeltaLake #ApacheIceberg #DataEngineering #Analytics #DataInfrastructure #DataPlatform #DataGovernance #CloudData #DataWarehouse #DataLake #BusinessTechnology #DataBusiness #FexingoBusiness #BusinessPodcast #DataPodcast

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Metric stores are becoming the backbone of consistent business metrics, bridging the gap between raw data and decision-making. In this episode, Lucas and Luna explore why companies like Airbnb and Shopify are turning to metric stores to define metrics once and reuse them across BI tools, feature stores, and reverse ETL pipelines. They break down the core concept—metrics as code—and walk through a practical example of how a mid-sized e-commerce company slashed metric definition time by half using a metric store with a semantic layer. Along the way, they discuss the trade-offs of adding another tool to the stack, the role of headless BI, and how metric stores complement existing data contracts and lineage efforts. If you're a data leader weighing whether a metric store is worth the hype, this episode gives you the concrete questions to ask before you commit.

#MetricStores #DataEngineering #SemanticLayer #BusinessIntelligence #DataProducts #HeadlessBI #DataGovernance #DataTeams #Analytics #DataInfrastructure #Airbnb #Shopify #MetricsAsCode #DataContracts #DataLineage #BusinessAndTechnology #FexingoBusiness #BusinessPodcast

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In this episode of The Data Business Podcast, Lucas and Luna explore how forward-thinking data teams are shifting from cost centers to revenue generators by building data products people actually pay for. Using the example of a regional bank that launched a portfolio risk API and a logistics company that turned shipment tracking into a premium subscription, they break down the real economics: pricing models, internal adoption, and the metrics that matter. They also discuss the common pitfalls—like building products nobody wants—and how to avoid them by starting with a specific customer pain. If you're leading a data team or selling data-enabled capabilities, this episode gives you a practical framework for turning data into a profit center without losing sight of your core mission.

#DataProducts #DataMonetization #Analytics #DataEngineering #RevenueOperations #Business #Technology #DataStrategy #PricingStrategy #CustomerCentric #DataDriven #InformationProducts #DataTeam #ROI #API #DataBusiness #FexingoBusiness #BusinessPodcast

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How do you put a price on a data product? In this episode, Lucas and Luna dig into the messy economics of internal data marketplaces, from cost-plus transfer pricing to value-based models, and how a handful of companies are experimenting with dynamic pricing to balance demand and compute costs. They get concrete: the story of a logistics firm that cut its data warehouse bill by 18 percent by charging business units per query, and the debate over whether the 'consumer pays' model kills innovation. Along the way, they look at why data teams are suddenly acting like mini finance departments, and what that means for engineers. Plus, a short note on how listener support keeps the show independent. If you're building or running a data platform, this is the episode for you.

#DataPricing #DataProducts #DataMarketplace #InternalData #CostPerQuery #DataStrategy #DataEngineering #CloudCosts #DataFinance #BusinessTechnology #DataLeadership #DataGovernance #DataMonetization #Analytics #TechBusiness #FexingoBusiness #BusinessPodcast #DataDriven

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In this episode, Lucas and Luna explore how data teams are shifting their cost optimization strategy from cost per query to cost per active user. They discuss the limitations of granular cost metrics, the importance of aligning data costs with business value, and how a fintech company reduced its data spend per active user by 30 percent by refining its data architecture and query patterns. The hosts also cover the challenges of implementing this metric, including data governance, attribution, and the risk of over-optimization. Tune in for a practical look at how data leaders are changing the conversation around data costs.

#DataCosts #CostPerActiveUser #DataAnalytics #DataInfrastructure #DataTeams #Fintech #DataArchitecture #QueryOptimization #DataGovernance #BusinessValue #DataStrategy #CloudComputing #DataEngineering #DataOps #FexingoBusiness #BusinessPodcast #Technology #DataManagement

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