Home › Data Analytics Services › Cloud Native Data Modernization For A Global Media Leader Case Study
Client
The client is a leading global media and entertainment conglomerate, with a diverse portfolio spanning streaming, sports, interactive experiences, and world-renowned content brands. Serving millions of viewers and guests worldwide, the organization is recognized for its commitment to innovation, technology-driven storytelling, and continuous expansion across digital and physical platforms.
As the industry faces shifting consumer preferences and growing competition, the client prioritized advanced analytics, operational efficiency, and agile technology adoption to support data-driven decisions, streamline global operations, and deliver engaging audience experiences at scale.
Market Trends in Media and Entertainment
In 2025, the global media and entertainment industry is undergoing rapid transformation, fueled by the rise of digital streaming, expanding international audiences, and growing competition from both established brands and new entrants. Companies invest in cloud-native data ecosystems and automation to unlock real-time insights, manage content costs, and deliver hyper-personalized experiences across diverse channels.
Key challenges include fragmented audience attention, evolving monetization models, and increased regulatory complexity. As leading organizations scale streaming and digital businesses, the ability to operationalize trusted data, while improving efficiency and business agility, has become essential for sustaining growth and maintaining industry leadership.
The Need For Change
The client’s legacy reporting environment faced critical limitations: scalability was restricted, maintenance costs were high, and manual, error-prone processes slowed data-driven decision-making.
Rising licensing costs, especially for ServiceNow, further pressured the need for a cost-effective, cloud-native solution. Migrating large datasets from ServiceNow to Snowflake was a strategic priority, enabling the client to decommission expensive systems and unlock greater analytics agility.
- High operational costs and reliance on legacy tools: Maintaining on-premises databases and proprietary extract, transform, and load (ETL) software led to escalating expenses and limited scalability as data volumes grew.
- Slow, manual reporting and delayed insights: Non-modular, redundant pipelines and outdated processes created bottlenecks, delaying analytics and impacting business agility.
- Inconsistent data quality and lack of trust: Siloed, unvalidated data sources resulted in unreliable reporting, reducing confidence in analytics for strategic decisions.
- Complex, time-intensive data migration requirements: Migrating massive ServiceNow datasets to a modern cloud platform required significant manual intervention, risking downtime and business disruption.
LTIMindtree Solution
LTIMindtree partnered with the client to architect a scalable, cloud-native data ecosystem, modernizing reporting and enabling cost-effective, real-time analytics at enterprise scale.
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Re-architected the reporting data platform
Migrated from on-premises and legacy ETL to an enterprise, load, transform (ELT) framework using Snowpark, supporting modular, index-based extraction for over 15 billion records and 20+ terabytes of data across 13+ ServiceNow modules. This enables scalability and supports future business growth.
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Automated, metadata-driven data ingestion
Developed a highly extensible and automated framework to extract, validate, and load data into Snowflake with minimal manual effort. This reduces operational overhead and accelerates time-to-insight for business teams.
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Enabled data validation and near real-time reporting
Integrated automated quality checks and streamlined pipelines, delivering over 95% data accuracy and ensuring business teams could access trusted insights in near real time.
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Retired costly legacy tools and platforms
Successfully migrated and deleted historical data from ServiceNow, eliminating expensive licensing costs and simplifying IT operations with a cloud-native, future-ready solution.
Business Benefits
Projected USD 2.5 Million in savings over three years
95%+ data accuracy and trusted analytics
Near real-time insights for business agility
Simplified IT operations and reduced manual effort
Scalable, future-ready data ecosystem
“Our partnership with one of the largest commercial property and casualty insurers in the U.S. reflects our shared vision for a data-driven, customer-first future. By modernizing their claims data platform, we’ve laid the groundwork for faster, smarter, and more seamless claim experiences for their policyholders. Together, we’ve built a foundation that drives operational excellence and elevates every customer interaction.”
— Prashanth Pulgal, Associate Vice President, Data & Analytics, LTIMindtree
Conclusion
The client’s move to a cloud-native, automated data ecosystem modernized reporting and analytics across its global media business. By eliminating legacy overhead, improving data accuracy, and enabling near real-time insights, it has strengthened its position as a digital innovator, empowering teams to drive faster decisions, optimize costs, and support future growth in a rapidly changing industry.
Ready to modernize your data platform for trusted, real-time analytics?
Explore more or contact us at data.analytics@ltimindtree.com.
