Future-Proofing European Asset Management Firm

Client

A UK-based asset management firm trusted by clients worldwide in finding future-fit investment opportunities to achieve the desired outcome.

Business Challenges

• Bring efficiency in Azure Resource Management and process optimization
• Data aggregation and easy access to data
• Gaining scalable and cost-effective data insight

LTM Solution

• Designed and architected a cloud-based platform that is cost-effective, scalable, and shareable across teams. 
• Data imported from data warehouses (SQL DW), MedM Platform (fund benchmarking software), Factset, Reuters, Google Analytics, and other sources using scheduled data factory pipelines. 
• CI/CD setup for script, data factory pipeline, and configuration table deployment. 
• Developed key vaults for storing everything confidential effectively. Access Control List (ACL) access was restricted. 
• Secured Azure resource's public network. A private endpoint was introduced. 
• ARM templates were initially used to facilitate cluster scalability in Azure HDInsight. 
• Offered Azure Databricks as a solution for cluster scalability, which outperformed Azure HDInsight in terms of features and performance while costing less and requiring less maintenance. 
• Automated cluster scaling via notebooks. Use of service account to control automated deployments. 
• Successfully hosted web applications such as labeling apps and red flags apps on Azure container Instance (ACI) and Azure app service.

Business Benefits

• Increased user base from 5 to 50+ in last year and is consistently increasing.
• Managed 5 clusters with 65TB of data in Data Lake compared to 2 clusters with 30TB of data in the previous year.
• Reduced overall DataLab cost from USD 26,000 to USD 10,000 approximately per month by moving to Azure Databricks from Azure HDInsight clusters.
• Reduced manual text labeling effort for data scientists by designing a text labeling tool and hosting it on Azure container instances.