The Data Business Podcast with Fexingo: Analytics, Data Infrastructure, and Information Products

In this episode of The Data Business Podcast, Lucas and Luna explore how data lakehouses are quietly resolving the long-standing war between data warehouses and data lakes. Anchored by the recent Databricks acquisition of Arcion for $100 million, they unpack what the lakehouse architecture actually is, why enterprises are adopting it, and how it changes the economics of data infrastructure. They w...

Lucas and Luna explore the hidden problem of data leakage in machine learning — when information from the future accidentally leaks into training data, inflating model accuracy and causing catastrophic failures in production. They examine a specific case: a major retail bank that launched a fraud detection model showing 98 percent accuracy in testing, only to see it fail in the real world because...

Podcast hosts Lucas and Luna explore how data clean rooms are transforming the way companies share customer data without compromising privacy. This episode focuses on a specific case: a major retailer and a consumer packaged goods brand using a clean room to run joint audience analysis while keeping raw data siloed. Lucas explains the technical architecture — differential privacy, query constraint...

Lucas and Luna unpack the rise of data version control (DVC) as a critical infrastructure layer for enterprise AI. They explore how tools like DVC and LakeFS are bringing Git-like versioning to datasets, enabling reproducibility, auditability, and collaboration at scale. The hosts walk through a concrete example: how a pharmaceutical company used data version control to track training data for a d...

When a major European bank discovered that its data lineage was manually tracked in spreadsheets, the compliance team spent 14 months untangling a single loan-origination pipeline. This episode examines how graph databases are replacing traditional catalog tools for data governance, using a real case from a financial institution that cut policy-audit time from weeks to hours. Lucas and Luna break...

Episode 24 of The Data Business Podcast: Lucas and Luna explore the shift from data-as-a-service to data product thinking in enterprise procurement. They break down how Snowflake's Marketplace and Databricks' Delta Sharing are turning raw data into packaged, priced products with SLAs. The conversation focuses on the concept of 'data product managers' and how companies like Fidelity and JPMorgan ar...

Lucas and Luna explore how data contracts are cutting integration costs for enterprise teams. They examine a case study from a major European retailer that reduced data pipeline failure rates by 60 percent within six months by implementing schema-level agreements between producers and consumers. The episode digs into why data contracts matter, how they differ from traditional service-level agreeme...

Lucas and Luna explore how data contracts are shifting enterprise software pricing from seat-based to usage-based models. They examine Snowflake's consumption pricing, Databricks' DBU model, and how companies like Fivetran and dbt Labs are adopting data contract principles to tie costs to value. The episode unpacks the economic logic behind usage-based pricing and the risks it introduces for both...

Lucas and Luna explore the rise of data marketplaces—platforms where companies buy and sell third-party datasets—and how they're reshaping business intelligence. They focus on Snowflake's Marketplace, launched in 2020, which now hosts over 2,500 datasets from providers like Knoema and SafeGraph. Lucas explains how this model lets companies enrich their analytics without building data pipelines fro...

Data observability is the practice of monitoring data pipelines for quality, freshness, and lineage in real-time. In this episode, Lucas and Luna explore how companies like Uber and Snowflake use observability tools to catch data quality issues before they cascade into expensive outages. The hosts break down the three pillars of observability—freshness, volume, and schema—and discuss why tradition...

In this episode, Lucas and Luna dive into the quiet revolution in enterprise software pricing driven by data contracts. They explore how companies like Snowflake and Databricks are moving from consumption-based to value-based pricing, using data contracts to define what customers actually pay for. The hosts examine a case study from a mid-sized fintech that saved 40% on data costs by implementing...

Lucas and Luna explore how synthetic data is transforming enterprise AI training, focusing on the case of a mid-size insurance company that slashed its model development cycle by 60 percent using synthetic data from a vendor called Mostly AI. They break down the economics — training on synthetic data cut their data-labeling costs by $1.2 million annually — and the technical trade-offs, including f...

Data mesh promised to decentralize data ownership and scale analytics across enterprises. But most implementations stall after the first six months. Lucas and Luna unpack why — looking at the gap between the architectural ideal and the organizational reality. They examine a specific case: a Fortune 500 retailer that spent $12 million on a data mesh platform only to see fewer than 15 percent of dom...

Lucas and Luna dive into the growing field of model observability—how companies monitor machine learning models in production beyond just accuracy metrics. They discuss the 2025 Aporia/WhyLabs survey showing 72% of enterprises have suffered a model-degradation incident costing over $200,000, and why traditional data observability tools miss ML-specific issues like data drift, concept drift, and fe...

Episode 15 of The Data Business Podcast explores a surprising shift: companies are starting to price data products based on the quality and reliability of the data, not just its volume. Lucas and Luna examine how firms like Snowflake and Databricks are experimenting with tiered pricing tied to data freshness and completeness, and what this means for data teams building internal dashboards and cust...

Episode 14 of The Data Business Podcast. Lucas and Luna explore how data contracts—formal agreements between data producers and consumers—are moving from niche engineering teams to enterprise-wide adoption. They examine a concrete case: a mid-size fintech that cut data pipeline failures by 40 percent after implementing schema-level contracts. The hosts discuss the shift from reactive data quality...

Episode 13 of The Data Business Podcast: Lucas and Luna dive into data observability — the operational discipline that separates companies that catch pipeline failures before they reach production from those that discover a broken revenue report at the quarterly board meeting. They explore why traditional monitoring isn't enough, how the five pillars of observability (freshness, volume, distributi...

Lucas and Luna explore how feature stores — centralized repositories for machine learning features — have moved from infrastructure nicety to operational necessity. They dive into the concrete case of a mid-sized fintech that cut model development time by 60 percent after adopting Feast, and discuss why feature reuse and consistency matter more than most teams realize. The episode also touches on...

Lucas and Luna explore the rise of data unions — collective organizations that pool personal data to negotiate with tech giants. They examine the Swash union, which has aggregated browsing data from over 100,000 members to sell insights to ad platforms, and discuss the regulatory implications under GDPR and the EU Data Act. The episode drills into the economics of data as labor, comparing union ba...

Episode 10 of The Data Business Podcast tackles the messy reality of data mesh adoption. Lucas and Luna unpack Zillow's failed 2021 migration to a mesh architecture, why domain ownership created new silos instead of breaking them, and the surprising metric that companies should track instead of 'data quality scores'. They also discuss how one insurance firm got it right by pairing domain data stew...

In this episode, Lucas and Luna examine how investment banks and corporate acquirers are now placing explicit dollar values on data assets during M&A transactions. Using the 2024 acquisition of Tableau by Salesforce as a reference point, they discuss a 2025 benchmark showing that companies with audited data quality scores commanded 12 percent higher multiples in private transactions. They also exp...

Lucas and Luna explore why data lineage — the ability to trace a data point from its source through every transformation — has become a regulatory and operational priority in 2026. Using the EU's latest financial reporting framework (ESEF 2.0) as a concrete case, they unpack how banks and fintechs are investing in automated lineage tools. Lucas cites a 2025 study showing that firms with mature lin...

Episode 7 of The Data Business Podcast dives into the real-world costs of testing data pipelines. Lucas and Luna examine a case study from a mid-size fintech company that discovered its data-quality testing suite was consuming 40% of its engineering budget—more than any other function. They break down the numbers: how testing time grew as data volume doubled every 18 months, the trade-offs between...

In this episode of The Data Business Podcast, Lucas and Luna dive into the quiet but tectonic shift happening inside modern data lakes: the rise of open table formats like Apache Iceberg, Delta Lake, and Apache Hudi. Lucas explains how these formats solve the decades-old problem of making cloud object storage behave like a transactional database, enabling atomic commits, time travel queries, and c...

In Episode 5 of The Data Business Podcast, Lucas and Luna examine the rising use of synthetic data in financial modeling and the hidden risks of model collapse. Starting with a real-world case from a mid-2025 algorithmic trading blow-up, they explore how synthetic datasets—artificially generated to mimic real market behavior—can silently erode model quality. Lucas explains the statistical phenomen...