Shifting to a single point of data access to extract value from cloud deployments

About

This company is one of the world’s leading food and beverage companies and has multiple brands generating more than $1B each in annual retail sales. This global conglomerate’s diverse portfolio of brands resulted in massive quantities of data. These brands stood to gain a lot from information about each other’s businesses and customers, but this data resided in different, proprietary systems.

Challenge

The food and beverage company had a problem. Roughly 95% of its data remained siloed within on-premises data warehouses like Teradata. The company needed a way to analyze both the new data streaming into Azure Data Lake Storage (ADLS) and this siloed data.

It took weeks to move data from the company’s Teradata warehouses into its data lake. Analysts couldn’t simultaneously query company data in ADLS and on-premises warehouses without costly ETL. When the team spun up a cluster with HDInsight, they had to leave it running, so they ended up paying for this cloud infrastructure 24/7.

Solution

The company turned to Starburst and Microsoft to help alongside Databricks. Starburst and Databricks offer highly complementary solutions. While Databricks handles Machine Learning

and streaming data ingestion into ADLS, Starburst provides a high-concurrency and

high-performance SQL query engine that integrates with multiple Azure data sources, in addition to relational and nonrelational databases, and various BI tools. 

Together, Starburst and Databricks ensure that the company extracts as much value as possible from its Azure deployment.

In addition, Starburst offers fine-grained security, fast performance, enhanced management and controls, 24×7 support from the Trino experts, and additional features that make it ideal for complex multinationals like this beverage giant.

Results

Starburst Enterprise and Microsoft ADLS have empowered this global food and beverage leader with a more efficient and scalable architecture for the future, including:

Self-service BI. The business intelligence and analytics teams can join and access data and tap into previously siloed sources to unlock hidden value and insights. 

Secure data sharing across brands. The ability to query and analyze other data sources at other brands — with fine-grained controls preventing unauthorized access — will drive new revenues and marketing programs across the company.

Cost savings through autoscaling. Starburst allows the company to meet user needs by automatically scaling up during busy times and scaling down at night and on weekends, so the company only pays for the Azure services it uses.

Faster time-to-insight. Business units, wholesalers, and brands can immediately access and query this data where it lies and join it with larger data sets.

Improved cluster management and chargeback. Starburst Enterprise allows the company’s data engineering services team to track every query and who runs it, then charge it back to the department.

The inexpensive, resilient, highly scalable storage of ADLS, along with the security enhancements and analytics anywhere capabilities of Starburst Enterprise are helping to move the company closer to its goal of becoming the global leader in convenient foods and beverages.