Ascend.io
Case Studies
Lumiata Case Study: Intelligent Pipeline Orchestration & Automation with Ascend
Overview
Lumiata Case Study: Intelligent Pipeline Orchestration & Automation with AscendAscend.io |
Analytics & Modeling - Big Data Analytics Analytics & Modeling - Data-as-a-Service Platform as a Service (PaaS) - Data Management Platforms | |
Healthcare & Hospitals | |
Product Research & Development Quality Assurance | |
Predictive Maintenance | |
Data Science Services System Integration | |
Operational Impact
Working from the concise, declarative codebase has made it faster to build new pipelines and relieves much of the maintenance burden for existing pipelines. | |
The data science team now has full visibility into the context of the data and resulting Curated Table. They can clearly trace operations done on data fields, and even pull in new fields or adjust the logic directly. | |
The ability to self-serve updates and experiment rapidly has allowed this team to become Citizen Data Engineers -- giving them more accurate models more quickly and relieving pressure from the central data engineering team. | |
Quantitative Benefit
Reduced the lines of code powering these pipelines by 98% | |
New pipeline creation was 7x faster | |
Process to go from raw data to Lumiata Insight is now 7x faster | |