Case Study

How a Global Entertainment Company Built an AI-ready, Governed Data Foundation on Databricks

Achieved 85% automated transformation and established domain-aligned data products without
any business disruption

The imminent need to break free from legacy constraints

A global live entertainment company relied on a complex legacy data ecosystem built on Teradata, Talend, and SAP BusinessObjects Data Services (BODS). Spiraling costs, slow ETL processes, and fragmented data pipelines limited business responsiveness. The company needed a scalable, governed data foundation to support real-time ticketing operations, accelerate entertainment analytics, and break free from the constraints of their legacy environment.

Key challenges:

  • High maintenance overhead: Legacy data warehouse, ETL, and BI reporting platforms increased both operational and licensing costs.
  • Legacy complexity: Siloed platforms and complex dependencies increased operational effort and costs, diverting resources from innovation.
  • Low operational agility: Rigid data pipelines constrained the ability to process fluctuating data volumes and respond quickly to fast-changing event demands.
  • Limited AI readiness: Fragmented pipelines constrained access to reliable, AI-ready data, limiting opportunities for advanced analytics and AI-driven innovation.

To accelerate insights, improve business outcomes, and unlock new AI use cases, the entertainment company set out to modernize its data estate to Databricks, while ensuring uninterrupted operations and preserving business-critical reporting capabilities.

Automated the end-to-end modernization journey – establishing domain-aligned data products for live entertainment, while driving 50% time and cost savings.

Establishing a connected, AI-ready data platform for entertainment operations

Data estate modernization equipped the global live entertainment company with a unified, scalable, governed Databricks foundation — enabling real-time access to reliable insights. The transformation ensured uninterrupted reporting while powering advanced analytics, faster decisions, and agentic AI innovation.

Business benefits

  • Greater business agility: Established a governed foundation on Unity Catalog, powering unified intelligence and enabling better responsiveness to changing business needs.
  • Domain-driven analytics: Consolidated fragmented pipelines, creating groundwork for reusable entertainment domain data products and more connected operational analytics.
  • Trusted performance insights: Strengthened data consistency and validation, providing a more dependable foundation for performance comparisons and coordinated operational decisions.
  • Minimized operational risk: Maintained business-critical data and reporting availability throughout the migration, protecting operational continuity and meeting all business SLAs.
  • Agentic AI-readiness: Unified siloed data assets, enabling AI systems and agents to access and consume previously untapped enterprise data for new use cases.

Overcame long-standing data processing and analytics barriers, unlocking a new chapter of AI-driven growth and innovation.

Powering automated modernization to a unified Databricks platform on AWS

The client leveraged Impetus LeapLogic™ Suite and Impetus Unity Catalog Migration Accelerator to fast-track and automate the end-to-end modernization journey to Databricks on AWS, delivering massive time, effort, and cost savings.

Automated data estate assessment: Impetus LeapLogic Assess helpedcut down the migration scope significantly with an in-depth assessment and profiling of existing inventory – eliminating dead code and redundancies.

Accelerated transformation at scale: LeapLogic Migrate seamlessly auto-transformed 1,200+ Teradata tables, 200+ workflows, 450+ dataflows, ~1,400 queries, 150+ stored procedures, 100+ macros, and 55+ SAP BODSto PySpark.

Custom ETL modernization: Converted 131 strategic ETL jobs (SAP BODS and Talend) into a custom Databricks-compatible YAML framework, enabling faster, more scalable data processing.

Unified data & governance foundation: Consolidated fragmented pipelines on Databricks, leveraging Unity Catalog and standardized data-handling practices to strengthen governance, scalability, and data consistency.

Preserved business reporting context: Modernized 16 SAP BusinessObjects (SAP BO) universes and updatedTableau connections, maintaining familiar reporting capabilities and continuity of business context throughout the transformation.

Strengthened data quality: Enhanced data quality through cell-level checks, naming-standard compliance, and comprehensive validation. Supported system integration testing, user acceptance testing, production deployment, and parallel-run execution to minimize migration risk.

Reduced operational complexity: Simplified the data estate with standardized pipelines and frameworks, reducing dependence on specialized legacy expertise and making future changes easier to implement.

Modernizing a Teradata, Talend & SAP ecosystem to a scalable Databricks architecture on AWS

Modernization gave the company a robust data backbone to support the pace and scale of live entertainment—from managing surges in ticketing activity to maintaining consistent performance visibility across events. It also laid the foundation for more agile, cost-efficient operations with lower licensing costs and maintenance overheads.