As an all-in-one package for standing up a data lake, it will take care of: 

• Cloud infrastructure: The accelerator comes with Terraform templates that deploy all the necessary infrastructure needed to build a lakehouse, including a Databricks workspace, networking, storage, key stores, and an orchestration tool.​ 
   

• DevOps: It has all the necessary DevOps components required to run a development, testing, and production environment. Including pipelines to test, approve, and push deployments into each environment.​ 
   

• Data pipelines and orchestration: Slalom’s technology takes advantage of metadata driven pipelines to reduce the time and effort needed to ingest new sources and extract all the value out of data. The accelerator includes all the needed parts to extract, transform, load, and curate datasets into the lakehouse paradigm.​ 
   

• Machine learning and curated use case framework: The accelerator is equipped with a framework to rapidly develop machine learning and curated use cases in a sandbox environment and provides processes to deploy them into production when ready. 

All of this simplifies loading data into a lakehouse, so data teams can focus on what really matters — extracting value from data. 

To learn more about how Slalom and Microsoft can make data management easier with Azure and the data lakehouse accelerator, contact us at moretogether@slalom.com.