At large enterprises, data resides in hundreds, sometimes thousands, of separate systems consisting of a combination of open-source, proprietary and tailored solutions — each with its own data model, speed, availability, and cost. How can this diversity — and the peak performance it delivers — be retained, while supporting one data visualization, data science and the ML/AI applications with one platform?
Starschema’s unique Antares data lake design is driven by a fully standardized internal model and offers the flexibility of accommodating an enormous range of enterprise systems as data sources.
In this white paper, we describe how our data lake design
- Provides real-time ingestion
- Ensures metadata management and data quality
- Incorporates automation, DevOps and Application Lifecycle Management
- Secures your data and helps meet compliance requirements
