Data Engineering

Leverage the power of data and AI to accelerate time-to-insights and time-to-value.

Home Practices Data Engineering

Delivering flexible, easy to extend and scalable data foundation

Enterprises need thoughtful data engineering to sustain AI & analytics at scale. Our digital accelerators are designed to accelerate the entire life cycle of data management, covering data ingestion, data quality, catalog, and data provisioning, focusing on improving time to value and self-service analytics for different user personas. In order to scale analytics and AI, you need Tredence to deliver a flexible, easy to extend, and scalable data foundation.

T-ingestor

A codeless Data Ingestion tool, T-Ingestor extracts data from a variety of transactional databases, data repositories such as data warehouses, structured and semi-structured files and any APIs. It is designed to load data into Azure Blob, Azure Data Lake Storage and Snowflake Database. Our T-Ingestor is fully integrated to check data quality, identify sensitive data leveraging algorithms, provide dashboards to monitor performance, volumes and other operational metrics.

Customer Explorer

Customer Explorer allows marketers and CX practitioners to create segments based on Customer 360 data (behavior, profile, predictions & third-party data). Then, analyze and use them for marketing/experience activation. It supports marketers in accelerating segmentation, accurate targeting, and boosting existing campaign/marketing tools.