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