TD:LR

A while ago we added the ability to upload an image to AgileData Disco, it was so customers could upload screenshots of their Dashboards and we could get Disco to document their Data Environments based on those images.

Talking to few a people yesterday reminded me I was going to test uploading an image of a completed Information Product Canvas to AgileData Disco and see if it would add any value in initial designs for the data environment.

So the hypothesis was:

“Can completed Information Product Canvas image help with the initial design of the data environment to deliver that Information Product.”

To test out the hypothesis I uploaded one of the canvas that I collaborated on to is being used as an example in the upcoming “an Agile Data Guide to Information Product Canvas” book.

As this canvas was based on a real world example of an Information Product somebody had already created for one of their customers, and I only facilitated the population of the cavas, this would reduce the bias in the experiment compared to me creating one from scratch just for this purpose.

Here is an interactive demo / guide showing the results of the experiment:

https://guides.agiledata.io/demo/cm7c9gj7h0jr49ujfhaymm0um

It is a quick and dirty interactive demo, where I test the process and then make notes on what I think worked and what we need to iterate.

An aside on the value of interactive demos

I have started using this interactive demo format a lot, much better than making disconnected notes, and also much better to see what each note relates to.

I can quickly document something and then share it with Nigel Vining and he can view it whenever he has time, great for our remote only, work from anywhere in the world way of working.

I have also been using this interactive demo pattern to log support calls with other vendors when I have a problem with their product.

As they say seeing is believing.

Back to the result.

Overall the Disco outputs were not good enough to be used as a data design (not sure it ever will be perfect), so some more iteration to be done.

But the output it did generate was an encouraging start.

Keep making data simply magical