mirror of
https://github.com/open-metadata/OpenMetadata.git
synced 2025-07-31 05:04:39 +00:00
d799d792a2
* migrate overview and restructure * Add latest release sticky * Add latest release sticky
86 lines
4.8 KiB
Markdown
86 lines
4.8 KiB
Markdown
---
|
||
title: Latest Release
|
||
slug: /overview/latest-release
|
||
---
|
||
|
||
# 0.11.0 Release - June 30th 2022 🎉
|
||
|
||
You can read the Release Blog [here](https://blog.open-metadata.org/openmetadata-0-11-release-8b82c85636a)
|
||
or watch an awesome video showing the new features!
|
||
|
||
<YouTube videoId="V_HkZsMkvho" start="0:00" end="8:03"/>
|
||
|
||
<br></br>
|
||
<br></br>
|
||
|
||
## Data Collaboration - Tasks and Emojis
|
||
|
||
Data Collaboration has been the prime focus of the 0.11 Release, the groundwork for which has been laid in the past
|
||
several releases. In the 0.9 release, we introduced Activity Feeds, Conversation Threads, and the ability to request
|
||
descriptions. In this release, we’ve added Tasks, as an extension to the ability to create conversations and post
|
||
replies. We are particularly excited about the ability to suggest tasks. This brings the collaboration to the next level
|
||
where an organization can crowdsource the knowledge and continuously improve descriptions.
|
||
|
||
## Column Level Lineage [#2931](https://github.com/open-metadata/OpenMetadata/issues/2931)
|
||
|
||
In OpenMetadata, we primarily compute column-level lineage through SQL query analysis. Lineage information is
|
||
consolidated from various sources, such as ETL pipelines, DBT, query analysis, and so on. In the backend, we’ve added
|
||
column-level lineage API support. The UI now supports exploring this rich column-level lineage for understanding the
|
||
relationship between tables and performing impact analysis. While exploring the lineage, users can manually edit both
|
||
the table and column level lineage to capture any information that is not automatically surfaced.
|
||
|
||
## Custom Properties
|
||
|
||
The key goal of the OpenMetadata project is to define Open Metadata Standards to make metadata centralized, easily
|
||
shareable, and make tool interoperability easier. We take a schema-first approach for strongly typed metadata types and
|
||
entities modeled using JSON schema as follows:
|
||
|
||
OpenMetadata now supports adding new types and extending entities when organizations need to capture custom metadata.
|
||
New types and custom fields can be added to entities either using API or in OpenMetadata UI. This extensibility is based
|
||
on JSON schema and hence has all the benefits of strong typing, rich constraints, documentation, and automatic
|
||
validation similar to the core OpenMetadata schemas.
|
||
|
||
## Advanced Search
|
||
|
||
Users can search by multiple parameters to narrow down the search results. Separate advanced search options are
|
||
available for Tables, Topics, Dashboards, Pipelines, and ML Models. All these entities are searchable by common search
|
||
options such as Owner, Tag, and Service.
|
||
|
||
## Glossary UI Updates
|
||
|
||
The Glossary UI has been upgraded. However, the existing glossary functionality remains the same, with the ability to
|
||
add Glossary, Terms, Tags, Descriptions, Reviewers etc...
|
||
|
||
On the UI, the arrangement displaying the Summary, Related Terms, Synonyms, and References has been changed. The
|
||
Reviewers are shown on the right panel with an option to add or remove existing reviewers.
|
||
|
||
## Profiler and Data Quality Improvements
|
||
|
||
Profiling data and communicating quality across the organization is core to OpenMetadata. While numerous tools exist,
|
||
they are often isolated and require users to navigate multiple interfaces. In OpenMetadata, these tests and data
|
||
profiles are displayed alongside your assets (tables, views) and allow you to get a 360-degree view of your data.
|
||
|
||
## Great Expectations Integration
|
||
|
||
While OpenMetadata allows you to set up and run data quality tests directly from the UI, we understand certain
|
||
organizations already have their own data quality tool. That’s why we have developed a direct integration between Great
|
||
Expectations and OpenMetadata. Using our `openmetadata-ingestion[great-expectations]` python submodule, you can now add
|
||
custom actions to your Great Expectations checkpoints file that will automatically ingest your data quality test results
|
||
into OpenMetadata at the end of your checkpoint file run.
|
||
|
||
## ML Models
|
||
|
||
In this release, we are happy to share the addition of ML Model Entities to the UI. This will allow users to describe,
|
||
and share models and their features as any other data asset. The UI support also includes the ingestion through the UI
|
||
from [MLflow](https://mlflow.org/). In future releases, we will add connectors to other popular ML platforms. This is
|
||
just the beginning. We want to learn about the use cases from the community and connect with people that want to help us
|
||
shape the vision and roadmap. Do not hesitate to reach out!
|
||
|
||
## Connectors
|
||
|
||
In every release, OpenMetadata has maintained its focus on adding new connectors. In the 0.11 release, five new
|
||
connectors have been added - [Airbyte](https://airbyte.com/), [Mode](https://mode.com/),
|
||
[AWS Data Lake](https://aws.amazon.com/big-data/datalakes-and-analytics/what-is-a-data-lake/),
|
||
[Google Cloud Data Lake](https://cloud.google.com/learn/what-is-a-data-lake#section-6),
|
||
and [Apache Pinot](https://pinot.apache.org/).
|