CUSTOMER STORY

How S&P Global is Building an Azure Data Lakehouse with Dremio

Reduced

query times by 70%

Cut

internal operational costs by 50%

Enhanced

data analysis and decision-making

The Business:

S&P Global is a market leader in analytics and financial information services, serving a wide array of industries with data insights crucial for strategic decision-making. Their IT Business Intelligence (BI) team is responsible for internal reporting, focusing on service management data, cloud financials, and asset inventory to optimize operational efficiency and cost management.

The Challenge

S&P Global faced significant challenges with slow query times, data silos, and escalating costs due to complex data manipulations and cube creation for Power BI. The reliance on Azure Cosmos DB for enhanced table functionality led to increased expenses and operational inefficiencies, hindering the team's ability to deliver timely and accurate internal reports.

The Solution

Dremio was chosen for its seamless integration with Azure Data Lake Storage (ADLS) and its ability to directly query data without unnecessary movement or duplication. The platform's user-friendly interface and compatibility with Apache Iceberg allowed for efficient data management and scalability. Dremio's self-service analytics capabilities and advanced data security features, integrated with Okta, streamlined user access and data governance.

"Our partnership with Dremio transformed our data strategy, breaking down silos and propelling our business forward with insights we didn't think were possible in such a short timeframe," said Tian de Clerk, Director of Business Intelligence at S&P Global.

Results

Implementing Dremio resulted in a 70% reduction in query times and a significant decrease in operational costs, freeing up the budget for other strategic initiatives.

S&P Global effectively cut their total running costs for the relevant internal operations by about 50%. This cost reduction is attributed to eliminating the need for Azure Cosmos DB, which was previously utilized to enhance table functionality but proved to be more expensive and less efficient for their needs.

By transitioning to Dremio and leveraging its capabilities, they were able to streamline their data operations and reduce infrastructure costs substantially, thereby halving the total expenses associated with running their internal data analytics functions.

The platform's scalability and self-service features enabled S&P Global's data engineers and analysts to access and analyze data more efficiently, leading to improved internal reporting and data-driven decision-making.

Conclusion

S&P Global's adoption of Dremio transformed their approach to data analytics, enabling the IT BI team to overcome significant challenges and achieve remarkable cost savings and operational efficiencies. By leveraging Dremio's scalable, user-friendly platform, S&P Global has set a new standard for data management and analytics within their organization, driving innovation and strategic decision-making.

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