Advanced Data Processing for a Global Media & Entertainment Leader
A multinational media and entertainment conglomerate set out to modernize how enterprise data powers decisions. With high-volume, fast-growing datasets spread across legacy systems, vendors, and formats, the organization saw an opportunity to create a single, governed, AWS-aligned data backbone that could serve analytics at scale, including Tableau visualizations across business units.
Partnering with Saxon, the company stood up a modern data-warehousing and processing environment that supports both current and future big-data workloads without disrupting live operations.
The Goals
Stand up a modern data-warehousing environment purpose-built for big data.
Establish robust ETL and data models to extract, unify, and govern data from internal/external sources.
Enable single-pane-of-glass analytics in Tableau backed by an AWS data lake.
Create a scalable processing layer (Hadoop/S3 + enterprise ETL) that absorbs legacy data and future growth.
Impact Delivered
A fit-for-purpose big-data warehouse with effective, cost-efficient storage and analytics.
Consolidated pipelines that unify reports from many sources into trustworthy, governed outputs.
Legacy-to-cloud migration of data into an Amazon S3 data lake via new ETL components and Sqoop-based loads to Hadoop.
A single visualization interface in Tableau, giving business teams a clearer, faster view of performance.
The full case study details the architecture, migration blueprint, ETL patterns, and operating model used to modernize at scale without disruption.
