One of the seemingly scariest changes moving to D365 a few years ago [when it was still AX7] was the loss of the constant in our lives that was AIF.  AIF was the crux of EDI – it handled inbound and outbound messages, had innate transactional scope at the message level regardless of complexity, and at the end of the day you just felt good and secure seeing a tangible [XML] file in a folder that you could, run, rerun, and archive.  

The other nice thing about AIF and XML documents is that you don't have to have a technical background to manage and understand them.  A formatted XML document is very easy to read and the message history and error log was readily accessible in AX.  Since catapulting to the cloud, every project I go on yields the same questions from AIF gurus of old, "What's a JSON?"  "What does ODATA even mean?"  

First, JSON means JavaScript Object Notation; the only thing you really need to get from that is that it's a format for writing stuff (in this case objects, such as sales order numbers, SKUs, amounts, etc).  At the end of the day, JSON is your new XML.  What used to read like this:

Now potentially reads like this:

Second, ODATA is short for Open Data Protocol.  If that doesn't mean anything to you, you might go down the Google rabbit hole of "What's REST?"  "What's SOAP?"  What's important to understand is that ODATA is used by a ton of humans (ie people you want to integrate with) and it supports JSON.  In an AIF-less world, ODATA is a mechanism for your EDI partner to [eg] get your customers' orders [$$$] in your system.

Even though ODATA and JSON aren't new to the world at large, the way they are implemented in D365 is still special.  Users [you] can use ODATA to query D365 data and get results in a JSON format from the convenience a web browser.  In my opinion, learning to master, or even fumble through this, is essential in an environment where you don't have SQL access.  You can visualize data at large, get record counts, and get empathy for your integration partners by seeing what they see.

Step one: Change the your environment URL to end with the word data instead of company id and menu object.  This will reveal a list of all the data entities available to you.

Step Two. If you know what you're looking for, append the entity name to your URL, otherwise hit CTRL + F and search stuff.  Let's say you loaded a giant movement journal and are asking yourself, "Is DMF doing anything? Is anything happening or is the system just spinning?"  Search for movement, and look for something meaningful.  You can always tie this back to a data project you made as well.

Step three.  Copy and paste the name into your url after data.  This is case sensitive!  In this example, becomes

Step four. Add filters.  To get the record count, you can add count to the end of the URL.  If you aren't sure whether that data project spinning or not, refreshing this will tell you if the record count is increasing (aka actually doing something).  

Bonus step.  Add a filter to your count.  You can have multiple filters and operators at the same time! Here is an example to check a record count (growing or not) for a specific journal:$count?$filter=JournalNumber eq '000001'

The possibilities are endless.  You can do cross company queries, sorts, and various operators.  The best resource for more details is here, but you can apply almost anything you read about ODATA outside of Microsoft Docs to your D365 instance.