Customer Case Study

SIRCA Technology provides big data storage, management, and analytics consultancy and solutions to the financial services sector. Their SIRCA Gateway Platform offers researchers the ability to access, analyze, and innovate with vast amounts of previously unavailable financial data.

Vertical Use Case

Predicting the impact of various events on financial markets

Technical Use Case

  • Data Ingest and ETL
  • SQL Analytics

The Challenges

  • Legacy infrastructure was extremely slow to access data and run reports which impacted the customer experience. For example, the data ingestion process could take hours at a time for a single query.
  • The level of DevOps effort to manage their infrastructure was too costly.
  • Inability to scale data manipulation and exploration which was performed on single machines with RStudio and SAS.
  • Several petabytes of global market and company financials data such as earnings reports were difficult to access.
  • Disparate data sets made complex queries which required the use of a third party tool to merge and manipulate the data. This was difficult, time-consuming, and impacted the quality of query results served to the end user.

The Solution

Databricks provides SIRCA Technology with a unified analytics platform that serves as the technology backbone of their customer-facing application. As a result, they are now able to deliver a modern data research and analytics platform for financial markets analyses.

  • The fully managed platform simplifies operations and reduces operational expenses
  • Databricks Runtime provides lightning fast data processing at scale
  • Interactive Workspace fosters collaboration across analysts and data scientists

The Results

The impact Databricks and Apache Spark has had on the performance of their application has been significantly improved, even at scale.

  • Able to easily and quickly ingest data at scale and serve it to their end users.
  • Automated job scheduler and interactive notebooks are core to powering their self-service application.
  • Leveraged autoscaling to easily meet unpredictable demands (from 2 nodes to 10 nodes with ease).
  • Fully managed cloud service allows their team to focus on higher-level issues related to their domain rather than DevOps work to build the underlying system.