The Operational Data Lake is a critical component in unlocking operational intelligence from the data lake. It enables organizations to efficiently capture and analyze unprecedented volumes of data generated from connected devices and users, while exposing that data to operational applications. The design pattern for operationalizing the data lake involves integrating an operational database with the data lake, leveraging technologies such as MongoDB, Hadoop, Spark, and Kafka. Real-world examples demonstrate how leading companies are using this approach to achieve significant benefits, including improved customer experiences, increased efficiency, and enhanced decision-making capabilities. With its flexible data model, powerful in-database analytics, distributed architecture, and low latency performance, MongoDB is well-suited to operationalize the data lake.