A list of data tools I use regularly, or look forward to testing out

Dear Data-Traveller, please note that this is a LinkedIn-Remix.

I posted this content already on LinkedIn in September 2022, but I want to make sure it doesn’t get lost in the social network abyss.

For your accessibility-experience and also for our own content backup, we repost the original text here.

Have a look, leave a like if you like it, and join the conversation in the comments if this sparks a thought!

Link to Post

Screenshot with Comments:

Screenshot of Timo Dechau's LinkedIn post with text about data tools

Plain Text:

Every week I discover new data tools. And I am a dangerous person when it comes to new tools. If I could, I would try them all. But I can’t….

So I try to avoid watching other people talking about new data products. But I usually fail because I love to see these.

So I did one myself. Video link in the comments.

In this video, I discuss the tools I am using and put them into four categories: Essentials, Road to Essential, Testing, and Testing Backlog.

Essentials are tools I use regularly. Here is the list of my essential tools:
– Google Tag Manager
– Avo
– Segment
– Amplitude
– Google Cloud Platform
– dbt Labs
– GitHub Codespaces
– VSCode
– Activity Schema (thanks to Ahmed Elsamadisi)

I explain how I use them, why I have chosen them, and what could challenge their status as essential.

On the road to Essential are these tools:
– Lightdash
– Preset
– PostHog
– Snowplow
– Walker.js (thanks to Ayla Prinz & Alexander Kirtzel)

I explain the use cases and what is missing for me to declare them as essential.

On the testing workbench, I have these tools:
– Keboola
– RudderStack
– Snowflake
– Hex
– Zing Data
– Cube
– Transform
– Elementary Data
– Cypress.io

I quickly explain what use case I am testing at the moment.

In my backlog for the following tests are these:
– Piwik PRO
– Metaplane
– DuckDB Labs
– Zingg.AI