Know how Tredence helped the client modernize its data infrastructure with Databricks Lakehouse and Azure
The client is a global food giant, providing solutions to food service and supermarket chains in 112 countries.
With over $4 billion in revenue and 2,000+ products, the company sought to modernize its data infrastructure to support agile decision-making and advanced analytics.
The client is a global food giant, providing solutions to food service and supermarket chains in 112 countries.
With over $4 billion in revenue and 2,000+ products, the company sought to modernize its data infrastructure to support agile decision-making and advanced analytics.
Siloed and Unprepared Data: Data was scattered across multiple systems (worksheets, Oracle databases, etc.), making it difficult to access and analyze.
Duplication of Efforts: Teams often repeated data cleansing processes due to a lack of standardized procedures.
Inconsistent Data Quality: The data existed in diverse formats, complicating efforts to ensure data quality.
Lack of Advanced Analytics Capabilities: The infrastructure couldn't support complex analytics, limiting actionable insights.
Tredence partnered with the client to implement a cloud-based, enterprise-grade data platform using Databricks Lakehouse on Azure. The solution included:
T-Ingestor: A codeless automated data migration accelerator that enabled seamless structured and unstructured data ingestion.
T-Assurer: A framework for automated testing of ETL pipelines, ensuring compliance with data quality standards.
Data Encryption: Secure encryption of sensitive HR, customer, and vendor data across all layers (Bronze, Silver, Gold) of the Lakehouse platform.
Unified Data Model and Automation: Established a unified data model, automated data quality, and prepared for AI/ML-driven analytics.
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