ODD Platform
  • Overview
  • Architecture
  • ODDRN
  • Features
  • Use cases
    • Data compliance for Data Scientists
    • Deprecation for Data Engineer \ Analyst
    • Visibility for Data Quality Engineer
    • Data preparation for Visualization Engineer
    • Service Provider and Pre-Sales
  • Configuration and Deployment
    • Try locally
    • Deploy to Amazon Elastic Kubernetes Service (EKS)
    • Configure ODD Platform
    • Enable security
      • Authentication
        • Disabled authentication
        • Login form
        • OAUTH2/OIDC
        • LDAP
      • Authorization
        • Policies
        • Permissions
        • Roles
        • Owners
        • User-owner association
  • Developer Guides
    • API Reference
    • How to contribute
    • GitHub organization overview
    • Build and run
      • Build and run ODD Platform
      • Build and run ODD Collectors
Powered by GitBook
On this page
  • About ODD
  • The platform for your business
  • Solution matrix
  • Pain points
  • Onboarding to data
  • Data discovery
  • Data observability
  • Features
  • Use cases
Edit on GitHub

Overview

NextArchitecture

Last updated 8 months ago

About ODD

The open-source Data Discovery Platform improves productivity, collaboration, and governance of modern data products and teams:

  • Free open-source and community-driven

  • ML first citizen

  • End-to-end microservices lineage support

  • Flexible data quality integration options

  • Auto-generated ML experiment lineage and metadata

To use Platform solutions more effectively apply . It contains best practices for managing your metadata. Its theoretical topics and examples help to build an effective data discovery process. Also the Spec covers data engagement and data federation problems.

The platform for your business

ODD's target audience is any data team regardless of its' size. It can be enterprises or large-scale companies challenging data mesh concept, small and mid-scale companies seeking OSS data catalogue solution and also DS teams aiming at better data governance. An ecosystem for all data team members. Platform functionality covers requirements of Data Scientists and Engineers, Product and Project Managers as well as Data Analysts, Architects, QA and BI Engineers.

Solution matrix

ODD can benefit a team at the following SDLC stages and team functions:

Pain points

Onboarding to data

Every time a newcomer joins a data team, one faces a challenge of data management processes learning. Unfortunately, it may provoke overcommunication, reading irrelevant documentation and spending much time to pick out meaningful information. ODD solutions help figure out data sources, find owners of this data, check DBs structures and get many other attributes that are necessary for working activities.

Data discovery

The more data a team has the more complicated connections occur between assets and components. ODD provides a search tool with AI-powered suggestion and flexible filters. Also the Platform supports a description option, so you can get detailed info about data entities.

Data observability

A problem of observability lack starts when irrelevant data appears in one's production cycle. To clarify when and where this data is and avoid delay use ODD's lineage diagram and flexible alert system.

Features

Use cases

Dive into ODD opportunities with a .

you can find most popular use cases for different titles of your data team.

list of ODD features
Here
ODD Specification