Data pipeline visualization

Hi,

I was wondering if there is a good tool for creating visual data pipelines on a high level for documentation purposes and to communicate with stakeholders.

I know that some tools provide visualizations of internal data pipelines like Apache Airflow, but am looking for a description of the big picture rather than debugging level information.

I am basically looking for a tool that creates visualizations of (multiple) data sources, intermediaries and destinations plus common operations like removing sensitive data, scheduling, speed, data throughput in MB etc.

Plus points if they follow a standard or look the same if they describe the same pipeline independent of who creates them.

For example:
MySQL RDS --every hour, takes 10 min, 100mb-> EC2 server with Airbyte --every hour, takes 10 min, 100mb, removes sensitive data-> Redshift

Cheers,
Johannes

Hello there! You are receiving this message because none of your fellow community members has stepped in to respond to your topic post. (If you are a community member and you are reading this response, feel free to jump in if you have the answer!) As a result, the Community Assistance Team has been made aware of this topic and will be investigating and responding as quickly as possible.
Some important considerations that will help your to get your issue solved faster:

  • It is best to use our topic creation template; if you haven’t yet, we recommend posting a followup with the requested information. With that information the team will be able to more quickly search for similar issues with connectors and the platform and troubleshoot more quickly your specific question or problem.
  • Make sure to upload the complete log file; a common investigation roadblock is that sometimes the error for the issue happens well before the problem is surfaced to the user, and so having the tail of the log is less useful than having the whole log to scan through.
  • Be as descriptive and specific as possible; when investigating it is extremely valuable to know what steps were taken to encounter the issue, what version of connector / platform / Java / Python / docker / k8s was used, etc. The more context supplied, the quicker the investigation can start on your topic and the faster we can drive towards an answer.
  • We in the Community Assistance Team are glad you’ve made yourself part of our community, and we’ll do our best to answer your questions and resolve the problems as quickly as possible. Expect to hear from a specific team member as soon as possible.

Thank you for your time and attention.
Best,
The Community Assistance Team