If you’ve ever built a BI solution it’s likely you will have had to integrate third party data, and if that’s the case you will know how painful it often is to get your hands on that data. Badly designed portals you have to log into every week to download the data, CSV files emailed to you, APIs with complex authentication – it’s usually an unreliable, slow and manual process.
Since my post last week on using the Google Image Charts API to create sparklines and small multiples in Power BI has proved very popular, I thought I would do a follow-up showing how to use the Azure Maps API to create map small multiples. Here’s an example of what’s possible, a table from a sample report I built that displays crimes committed in London (sourced from here) in June 2018 with one row for each crime and a map column displaying the location of the crime:
In the previous post we looked at enabling the built-in integration of Dynamics NAV and Time Series, which uses a Machine Learning (ML) model to predict inventory or cash requirements. This time we will make a very basic example with the sole aim of sending data from Dynamics NAV as input into an ML model that is running as a web service, and receive a result back from the model.
This post is a summary of what was new already in Dynamics NAV 2017: Using “Microsoft Azure Machine Learning Studio” to create (load) and then publish a model which we will call from Dynamics NAV to make inventory or cash forecasts. This is the model which is already available:
You know you have heard about it, Microsoft Azure, but what is it again? With all the new technology constantly being developed and advertised, it is easy to become lost in the acronyms, buzzwords, and concepts. Information describing Microsoft Azure can be overwhelming and intimidating.
I won’t be publishing the slide-deck directly, as Luc will soon publish both the slide deck, and the session recordings on Mibuso and YouTube, so you’ll be able to get your hands on that part. What I am publishing, though, should be quite enough for you to get your hands on my Azure Functions demos:
Running NAV inside a Container has many benefits but one of the probably most obvious ones when you start to work with it is the ease of deployment: Running a NAV container with SQL and WebClient embedded is as easy as docker run -e ACCEPT_EULA=Y navdocker.azurecr.io/dynamics-nav1. But that assumes that you have Docker installed and running and to keep it running you’ll need to maintain it.