Azure Synapse

CastorDoc and Azure Synapse

Azure Synapse Analytics is a fully managed cloud data warehouse.

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Why Castor x Azure Synapse makes sense?

Azure Synapse search experience is not optimal. End users often end up lost in all the Dashboards when they are looking for a specific content. One of the reasons is that lineage and popularity of Dashboards is not leveraged to organise these assets. It is hard to trust and have visibility in the Azure Synapse UI.

Castor makes it easy to find data the most relevant data assets with a powerful search optimized thanks to popularity and advanced filtering options. Castor also provides lineage between the data warehouse tables and Azure Synapse dashboards and questions.

How does it work?

This feature aims at displaying Azure Synapse's Dashboards within Castor, linking them with the tables they use and leveraging their popularity for search purposes.

Use-case #1

As as Sales Manager, I want to be able to find the MRR dashboard based on a search query and their popularity so that I can get a faster analytics insights

Use-case #2

As a Customer Success Ops, I want to be able to find the most advanced/popular data asset for my need and be guided in how to use a dashboard if needed

Ok, but what does it change for me?

Thanks to the Castor x Azure Synapse integration, you have better control, trust and visibility on your data infrastructure. This helps with:

  • Decreasing the number of duplicate content and work
  • Decreasing "Time to answer" as users can use the highest value add asset available (they don't use a table anymore when a dashboard is available)
  • Increasing the ability to deploy self-served analytics to less technical users

GET STARTED IN MINUTES, WITH YOUR FAVORITE TOOLS

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See Why Users Love CastorDoc
Fantastic tool for data discovery and documentation

“[I like] The easy to use interface and the speed of finding the relevant assets that you're looking for in your database. I also really enjoy the score given to each table, [which] lets you prioritize the results of your queries by how often certain data is used.” - Michal P., Head of Data