Welcome to the EzUA Tutorials repository! This is the official source for demos and tutorials related to the EzUA platform. The HPE Ezmeral Unified Analytics Software is usage-based Software-as-a-Service (SaaS) that fully manages, supports, and maintains hybrid and multi-cloud modern analytical workloads through open-source tools.
The software separates compute and storage for flexible, cost-efficient scalability to securely access data stored in multiple data platforms through a simple user interface, which is easily installed and deployed in minutes on private, public, and on-premises infrastructure.
Whether you're a beginner or an advanced user, you'll find useful content to help you make the most out of EzUA's capabilities.
This repository adheres to the versioning scheme of the EzUA platform. The develop branch serves
as the hub for active development. Release branches are derived from the develop branch, aligning
closely with EzUA versions. For instance, release-x.y.z is designed to seamlessly woth with EzUA
version x.y.z. It's worth noting that when you clone this repository, the default branch aligns
with the most recent EzUA version. Therefore, if you're working with the latest EzUA iteration, you
can clone it and proceed without the need to switch branches.
This repository is organized into two main directories:
- Demos: Tutorials that demonstrate how to integrate various frameworks like Kubeflow, Feast, Spark, and MLflow within the EzUA platform.
- Tutorials: Specialized tutorials tailored to specific frameworks and tools.
Navigate to the demos directory to find a collection of demos that cover a wide array of topics in analytics
and data science. These demos are designed to help you grasp what the EzUA platform offers.
For tutorials that are tailored to specific framework and tools, go to the tutorials directory. You'll
find specialized guides that show you how to leverage EzUA's frameworks and tools for particular use-cases.
The current list of framework-specific tutorials include:
- FEAST feature store: Ride sharing tutorial
- Superset: Data connection and visualization
To get started you need access to an EzUA cluster. Then:
- Navigate to the desired directory,
- Follow the respective README file for further instructions.
These demos and tutorials assume you have a basic understanding of the Python programming and some familiarity with analytics and data science concepts. Each guide may have additional specific requirements, which will be detailed within.
