tool
/
sqlflow_public
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
sqlflow_public/platforms/datahub
History
j 979e222e68 first commit 2024-10-23 17:52:59 +08:00
..
datahub-sqlflow-dbt-customers-gudu-sqlflow-column-level-result.png first commit 2024-10-23 17:52:59 +08:00
datahub-sqlflow-dbt-customers-gudu-sqlflow-column-level.png first commit 2024-10-23 17:52:59 +08:00
datahub-sqlflow-dbt-customers-gudu-sqlflow-table-level.png first commit 2024-10-23 17:52:59 +08:00
datahub-sqlflow-dbt-customers-gudu-sqlflow.png first commit 2024-10-23 17:52:59 +08:00
datahub-sqlflow-dbt-customers.png first commit 2024-10-23 17:52:59 +08:00
datahub-sqlflow-dbt.png first commit 2024-10-23 17:52:59 +08:00
readme.md first commit 2024-10-23 17:52:59 +08:00

readme.md

Integrate Gudu SQLFlow with Datahub

DataHub is an open-source metadata platform for the modern data stack.

Gudu SQLFlow is a powerful data lineage tool.

Integrate the Gudu SQLFlow with the Datahub enable you easily understand the end-to-end journey of data by tracing lineage across platforms, datasets at the column level.

We have built a test envionment so you can see how Gudu SQLFlow works with the Datahub.

Demo

Please login Datahub with Gudu SQLFlow with username: datahub, password: datahub

1. After login, just click the dbt icon

datahub-dbt

2. Select the customer table

datahub-dbt

3. You will see the Gudu SQLFlow tab

datahub-dbt

4. Click the Gudu SQLFlow tab to see the upstream and downstream of this table

datahub-dbt

5. Check the column level lineage by click the lineage item

datahub-dbt

6. See the full column level lineage

datahub-dbt

Feel free to contact us if you like to integrate the Gudu SQLFlow into your datahub platform and gain the ability to trace column-level data lineage.