117% ROI Unlocked and Accelerated AI Innovation with a Data Lakehouse on Google Cloud

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As specialized AI models and agents reshape business operations, traditional data architectures are struggling to keep pace with the demand for scalability, agility, and governance. Siloed legacy systems often result in data duplication, rising infrastructure costs, and slowed innovation. This Forrester Consulting Total Economic Impact™ (TEI) study commissioned by Google analyzes how building a data lakehouse with Google Cloud’s BigQuery and BigLake enabled organizations to get the flexibility of a data lake with open table formats like Apache Iceberg and the performance and governance of a high performance data warehouse, delivering the best of both on a single, open platform.

Forrester’s financial analysis reveals that a composite organization adopting this architecture achieved a Net Present Value (NPV) of $33.6 million, a return on investment (ROI) of 117% over three years, with a payback period of less than six months. In addition, the analysis uncovered significant enterprise value unlocked from unified governance and an integrated data and AI platform to accelerate innovation. Download the full study to discover how a high performance data lakehouse on Google Cloud transformed economic outlook and data strategy.

Key benefits realized by the composite organization in the study include:

Significant cost reductions: Eliminated up to $14.9 million in annual legacy infrastructure costs and avoid expensive data duplication by consolidating onto a cost-effective, serverless architecture
Enhanced workforce productivity: Achieved a 38% productivity gain for data engineers and a 35% gain for data analysts by unifying data access and simplifying pipeline management
Business growth through AI: Drive $17.5 million in incremental profit by unlocking new AI/ML use cases, accelerating time-to-market, and improving customer acquisition strategies