Supercharging AI with Exasol & Ibis
Exasol is excited to announce the launch of our new Ibis connector, now available in AI Lab! Together, Exasol and Ibis provide a powerful yet lightweight solution for AI development using production data at scale—easy to implement and easy to use.
What are Exasol and Ibis?
Exasol is a lightning-fast analytics engine that offers exceptional performance for interacting with data at scale. Ibis is an open-source Python library that allows users to power data frame workloads using a variety of back-end data platforms.
With Ibis, data scientists can leverage the full power of Exasol’s in-memory data engine for high-speed queries, data transformations, and machine-learning workflows. No more waiting for your local machine to struggle through large, complex manipulations.
Overcoming AI Development Challenges
Data scientists frequently use Python to create and manipulate data frames as part of AI & ML development. Tools like Jupyter and Hex give data scientists powerful environments for developing AI assets, but they are still often limited to local data for discovery and training purposes. Too often, data scientists are iterating on ML assets using data downloaded on their own machines – which can quickly become stale and lacks the scale necessary to train effective models. Working with larger, more comprehensive datasets provides richer training data to support more impactful AI development.
AI Development at Scale
The data necessary for production AI development often cannot live on a local data scientists’ machine – for size or security reasons. However, implementing production-level data pipelines to power AI development is complex and resource-intensive. Exasol and Ibis, alongside Exasol’s AI Lab – provide and end-to-end suite for data discovery, data science iteration and AI & ML deployment.
Get Started with Exasol’s Ibis Connector
It’s fast and easy to get started with Exasol’s AI Lab – full download and configuration instructions are available here: https://github.com/exasol/ai-lab/blob/3.1.0/doc/user_guide/editions.md
