Enterprises today are awash in data and under pressure to turn it into actionable insights — fast. To stay competitive, they’re modernizing their data infrastructure and adopting advanced tools to support real-time analytics, machine learning (ML), and artificial intelligence (AI).
For many of the world’s leading enterprises, the path forward runs through Fivetran and Databricks. These platforms are helping organizations automate data integration, centralize analytics, and power scalable, AI-driven decision-making.
Companies like Condé Nast, National Australia Bank (NAB), and Red Ventures are leading the way, streamlining operations, optimizing decisions, and unlocking new growth opportunities. By using Fivetran to centralize data from dozens of sources into Databricks and applying ML models, they’re delivering personalized experiences, enhancing customer engagement, and achieving operational excellence.
Condé Nast: Unified customer insights open new revenue streams
Condé Nast — the global media powerhouse behind Vogue, The New Yorker, and more — manages trillions of data points from hundreds of millions of readers around the world. But siloed systems, custom ingestion scripts, and fragmented data made it difficult to fully understand audience behavior or seize new revenue opportunities.
By implementing Fivetran, Condé Nast automated the integration and transformation of data from over 20 sources into Databricks Delta Lake, creating a centralized analytics platform. From there, they mapped customer journeys across brands, tracked real-time engagement, and generated actionable insights.
The result: improved operational efficiency, stronger content strategies, and higher returns on paid media spend. Condé Nast has even opened new revenue streams through data-driven advertising products and targeted campaigns.
Their modern data stack now powers data-informed editorial decisions that enhance both reader engagement and advertising performance, keeping them ahead in an ever-evolving media landscape.
Key results:
- Seamless ingestion of 20+ critical data sources and trillions of data points into Delta Lake
- Elimination of manual scripts and weeks of annual connector maintenance
- Faster generation of revenue-driving insights into digital audience behavior
“With Fivetran, we can pull data from pretty much anywhere and put it anywhere. This gives us a true 360-degree view of how our audiences are engaging with our content that we can then use to gain valuable insights into our audiences across brands.”— Nana Yaw Essuman, Sr. Director of Data Engineering at Condé Nast
Read the case study: Condé Nast maps customer journey across global brands with Fivetran
National Australia Bank: Elevating customer experience with generative AI
National Australia Bank (NAB), one of Australia’s largest financial institutions and a Fortune Global 500 company, serves more than 10 million customers and manages over $100 billion in assets. As it innovated in digital banking, NAB wanted to enhance customer experiences with AI, from intelligent chat assistants to fraud detection and campaign optimization.
But legacy systems and data silos stood in the way, driving up costs and causing service disruptions.
Fivetran enabled NAB to simplify and secure data integration from over 200 siloed sources into Databricks. With centralized, high-performance data and access to ML tools, NAB was able to scale its AI efforts, improving customer service and operational agility.
Their AI-powered chat assistant now delivers faster, more accurate support, while real-time fraud detection algorithms help proactively mitigate risk.
Key results:
- 50% reduction in data ingestion costs
- 30% increase in ML model performance and ad hoc SQL queries
- 1,000+ users onboarded and accessing data
“[Fivetran allows] us to unlock additional value and securely move our sensitive data to Databricks, so we can enrich it and drive insights without data leaving our own secure environment. [...] Fivetran enables us to provide the best customer experience with fresh, reliable, and compliant data.”
— Joanna Gurry, Executive of Data Platforms at NAB
Read the case study: National Australia Bank enhances customer experiences and powers GenAI
Red Ventures: Scaling with predictive AI/ML to increase cost efficiency 30%
Red Ventures’ Red Digital division, one of the largest digital marketing agencies in the world, needed a way to scale while keeping its marketing highly personalized. The solution? Better segmentation and predictive analytics, powered by centralized data and ML.
With Fivetran, Red Ventures automated the integration of over 40 data sources into Databricks, building a unified platform for customer analytics. ML models helped identify behavioral patterns, enabling precise segmentation and tailored marketing campaigns that increase ROI and customer retention.
By gaining real-time insights and automating key workflows, Red Ventures now supports 30% more clients without adding headcount.
Key results:
- 100+ hours saved per data integration
- 80% reduction in data processing time
- Improved campaign targeting with predictive insights
“With Databricks, Fivetran, and dbt, we can use data and AI in ways that help us reach the right customers with our clients’ marketing campaigns. That means we can deliver better results for their investment.”
— Brandon Beidel, Director of Product Management at Red Ventures
Read the case study: Red Ventures supports 30% more clients without new headcount
Building a future-ready enterprise with Fivetran and Databricks
Condé Nast, NAB, and Red Ventures are proof that modernizing your data stack isn’t just a technical upgrade; it’s a business advantage. With automated data integration from Fivetran and centralized analytics and ML from Databricks, companies are transforming how they operate, serve customers, and scale.
These organizations aren’t just keeping up — they’re setting the pace for what’s possible with AI and real-time data.
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