Unlocking SharePoint Connectivity in JMP Using Data Connectors (2026-US-30MP-2934)

Hello, everyone. Thank you for coming to my talk today. Today, I will be discussing Unlocking SharePoint Connectivity in JMP Using Data Connectors. My name is Will Morgan. I'm an Associate Software Developer with the Data Connectors team here at JMP.

To begin, I'm going to give a brief overview about what I'll be talking about today. I'll begin by giving an overview of SharePoint and OneDrive, what they are, how they might exist in your current workflow, and then how we can use it in JMP. I'll then move into a brief demo where I will be discussing the JMP Marketplace, the installation and configuration of the SharePoint add-in, as well as the utilization of Query Builder to modify your data whenever you're importing. Then I will move into a frequently asked questions walkthrough and some common troubleshooting steps that could be useful if you're having any issues with configuring your data connector.

I have a few key takeaways that I would like for you to walk out of this talk with. The first being to be able to install and configure the SharePoint Data Connector. Secondly, I want you to be able to create faster workflows using SharePoint Data. Finally, I want you to be able to understand common configuration issues that people have with these data connectors and ways you can help resolve them.

An overview of SharePoint and OneDrive for those that are unfamiliar with it. There are three different pieces of SharePoint, which is Microsoft's cloud storage data solution. We have SharePoint sites, lists, and then OneDrive. You may be familiar with one or all of these, but just to give a brief overview, SharePoint sites are collections of documents and document libraries that are typically accessible between different teams. Multiple people typically have access to the files that are stored here.

SharePoint lists are typically owned by the singular user that created them, and they can be shared between users. These typically hold tabular data. Things like form responses and other forms of tabular data can be stored within SharePoint lists. OneDrive is similar to SharePoint sites, except you are the owner of all the data here, and it needs to be shared manually.

All three of these options have some things in common, that being all the documents are stored online and they're accessed through web APIs. This means that the documents need to be downloaded manually from your browser before JMP can access them. This typically will slow down your workflow by requiring you to leave JMP and then come back into JMP, do your analysis. You'll see in a bit that this can be quite a clunky process if you're having to work with updated and refreshed data quite frequently. The SharePoint and OneDrive data connectors add-in, we aim to streamline this process and improve your workflow efficiency.

Why a data connector? Firstly, importing and exporting can be easily scripted and automated through JSL. That allows for easy data refreshing without any manual hassle of having to download the files. The exporting feature is a JMP 2027 only feature, so keep that in mind. Data connectors also allow refreshing of published tables to JMP Live. This is also a JMP 2027 only feature.

There's a few exciting things coming for this add-in and more. That's just another reason to get JMP 2027 whenever it comes out. Like I said earlier, it allows your workflow to stay entirely in JMP without having to switch between applications. You can increase your workflow efficiency through this way.

What the typical workflow in JMP would look like when using this data connector, you would begin by installing the data connector, which would be done through the JMP Marketplace, which I'll show during the demo. You would then configure your data connector using the Data Connectors Menu. You can then query your data using the JMP Query Builder. You would then analyze your data using the JMP Data Table or whatever JMP platforms you're already familiar with.

Then, once again coming in JMP 2027, you'd then be able to upload your data back to the SharePoint drive, whichever it was downloaded from. You end up with a cyclical process that can work really well of downloading your files, doing your analysis, and then exporting them back so that other people can have that updated data table that you might have changed.

Now I'm going to go into a brief demo. We will begin by opening up JMP. But before we get into that, I'm going to show you what the process looks like for downloading the files manually and then importing them into JMP and doing your analysis that way. Then we'll give it a comparison to what it's like using the data connector and how that can be used to increase your workflow efficiency.

As you can see here, this is my OneDrive. I've got a few files here. I've got a folder called JMP Test Data. I'm going to want to have a few files in here that I want to import into JMP and do an analysis on. I've got two tables here: Customers and Rentals. I'll select those, and then I'll click Download up top.

Then we can see in my Downloads folder, I have these two tables. Now back in JMP, I can go to File, Open, and then I'll find that folder where they were downloaded, select those two tables, and then I'll open those up. As you can see here, we've got two tables that were open in JMP. We have a matching column here called Customer ID, and I'm going to want to join these tables together to do an analysis on the age of a customer versus the number of days out that they rented a movie for.

In order to do that, I'll come to Tables, JMP Query Builder. Then in this menu, I'll add g6_Customers as a secondary table. I'm going to want to come over here to the Join button, and I'm not going to want to include any non-matching tables from either table. I want to do an Inner Join there. Then we can click Build Query. Then, like I said earlier, I really only care about the age versus the number of days out, so I can drag those two columns over here.

While I'm here, I'll go ahead and give a brief overview of the other features that Query Builder provides. You can also filter. You can say if I only wanted days out that are greater than 10, these are just the different types of filters that we have available, and as you can see, the SQL is updated in real time that is run in the background for these queries.

For the purposes of this demo, I don't need any filter, so I can just click Run Query. As you can see here, I've got a new data table with age versus days out from each of the two tables with about 518,000 rows.

Now I actually want to build a pretty simple graph based on this. I'll go Graph Builder, and I'm going to plot age on the x-axis, days out on the y-axis. As you can see here, it seems like there's a steep drop-off between ages 50 and 60, around age 55, where people don't seem to be having it out for as long. Maybe as people retire, they watch movies more quickly. It can give you analysis like that as well.

This was the workflow when you don't have the data connector installed. You might have noticed that the process of having to manually download your tables and import them into JMP could get a bit tedious whenever we want to have an updated version of the table. Say someone else added a few rows, then uploaded it back to your OneDrive, you'd have to redownload them from the browser and go through this entire process manually.

To avoid that and to help augment your workflow, we are going to now go over using the data connectors add-in for it. I'll also go over some configuration steps to help you with that as well. To begin by working with the add-in, you can go into the JMP Marketplace, which is marketplace.jmp.com. The JMP Marketplace is a very powerful platform that JMP provides, which provides many different add-ins to JMP with many different features such as data connectors and many other things.

To get to the SharePoint Data Connector, you can simply search for SharePoint. Then that'll take you to the landing page here where you can download the connector. But before I do that, I just want to briefly go over that. The Marketplace documentation here for this download page has a lot of very useful information to help you connect and work with this data connector. A lot of that, I'll be going over today. But if you need a reference, this is definitely the place to look if you need a reference for how to configure any of the options.

We can go ahead and click Download here. If you're not signed in, it'll prompt you to sign in. Then we will agree to the terms and conditions. Then there's a little survey here you can fill out. I'll just say I learned about this from the JMP Marketplace. Now that is on our file system, we can go back into JMP, click File, Open, and now we've got a new add-in here. Then we can click Install. Now this is going to prompt me to install the add-in. We can click OK.

In the background, this is going to be installing all the Python packages and scripts required to run the data connectors. It may take a second depending on your internet speed. But after that is done, it should give us a confirmation dialog that the installation was successful.

We've got that confirmation dialog that the installation was successful. We can click OK through that. Now I'm going to go over the connector options and how you can configure them. To get to that menu, you can go to File, Connect To, Data Connectors. We've got the Data Connectors menu here. You can click New Connection. Now we should see a few new options here. We have OneDrive demo, SharePoint list demo, and SharePoint site demo. These are the pre-configured connectors that I have. You'll see SharePoint_DC, OneDrive, SharePoint list, and SharePoint site.

These are going to be the ones that you're initially going to work off of. But the options that I have here for these are the same, so I can walk through these briefly with you. Going from the top down, the Client ID here is an optional value that can be used to configure if you need to have a custom authorization app hosted within your own Microsoft servers, and I'll give a little more detail on that whenever we connect here, and we go through the login page. But just know that the Tenant ID and the Client ID here are optional values, and they work together whenever you need to do this.

The File Filter is pretty self-explanatory. It simply will filter out any files that match the glob style pattern string that you put in here. This file filter that I've got on this connector will basically just find any files that match with a .jmp extension, so I only want JMP tables.

The Folder here is a parameter that tells the data connector where to look within your drive, and I'll have a visual example of this in a moment. But just a simple slash will tell the data connector to look through your entire drive. But you could have this filter down to a more specific folder if you have all of your data stored in a very specific folder and you don't want it to search through your entire drive.

Has Schemas here. If it's enabled, it will treat any folders underneath this configured one as schemas. It maps very similarly to a more traditional database with schemas and tables. It allows you to dynamically select different folders whenever you have a connection, if you have tables in a few different folders that you wanted to work with.

The Tenant ID, as I mentioned earlier, goes along with that Client ID. The username is useful for tying your token to the account that you want to work with for the connector. Then Verify SSL is an option that you probably won't need to mess with. But if you're having trouble with your SSL verification, you can disable that there.

To walk through the connection process, I'll go ahead and click Connect here. As you can see, the default browser is brought up with a login prompt to sign in to your Microsoft account. This is where you may run into issues where you need the Tenant ID and Client ID, because if you log in… It shouldn't have any issues with me since I have a JMP email. But if you have one of your own, and then you try to log in with this connector, it could prompt you that the connector is not verified within your tenant. If that is the case, you might need to have a Tenant ID and Client ID that is associated with your tenant that you would need to configure to the connector there. I'll have more information on that later, but there are a few other options for that as well.

But as you can see here, I have it searching through my entire drive. If we go back to my OneDrive, you can see that these schemas are all of the folders that I had underneath that configured folder. If you remember from earlier, I had a few tables in JMP Test Data, which is here. I have g6_Customers and g6_Rentals.

I'll go ahead and open g6_Customers. This is going to be that same table that we had before. To move on, I will show you the SharePoint site connector because there are a few different options here that the SharePoint OneDrive connector does not have. For SharePoint sites, we have a check-in comment here, which is basically a value of SharePoint sites. You can check out files, and if you do so, it will lock any other users from editing the file if you have it open in JMP. Then it will check back in that file whenever JMP closes on your computer. You can provide that comment there to say what you changed with the file whenever you want to check it back in.

The Tenant ID and Client ID are also both present and serve the same purpose as the OneDrive connector. The Folder also serves a very similar purpose, as well as Has Schemas, except they are tied to the document library here that you specify within your SharePoint Site. I'll show that with the example that I've got configured here.

The site URL is also a very important piece for this SharePoint connector. To show where we're getting that from, I can go to this JMP data connector SharePoint site that we have configured here for testing. In order to get the site URL that you want to have configured for this connector, you basically really just need to copy it from the URL page here. From the home page of your SharePoint site, it should have a very similar look to this where it has your domain/sites/the name of your site, which I have there. Then here are your document libraries on the side, so we have a Documents library. I'm going to want to check through these folders for any files that we may have.

We also have that Username and Verify SSL as well. If we connect to this, as you can see, it does not prompt us to log in again because that token that we requested from the OneDrive, since it's the same Microsoft account that you're using to log in, it's cached on the file system, so you don't need to go through the login process every single time.

But for the purposes of this, I wanted to go ahead and open up Rentals from the SharePoint site. I opened it from two different data connectors for a reason, because I wanted to show that you can open up files and tables from two different data connectors and join those together with Query Builder as well. That's an additional powerful feature of this, is that you can combine data from different sources in SharePoint and do a singular analysis on them through a singular script, which I will show here.

It's a very similar process as before with the local tables. We can change our query to do the Inner Join. We can build that query. We want age and days out. We'll just go ahead and run it. As you can see, we have the same table there as we had before. However, I'll go ahead and show the benefit of this, which is this source script here that we get from these tables. This generates a JSL script which uses New SQL Query in the background, which will dynamically grab these tables and do the join and everything needed that we just did through the user interface.

For example, if I click Run there, we get the same exact table there. This is the powerful feature of the data connectors. Say, for example, I took my Customers table here. To simulate data being changed in OneDrive, we'll just select a few rows here, and we'll just delete those guys. Then we can save this table. I'm going to go back to my JMP Test Data here. I'm going to delete this Customers file, and I'm going to re-upload this one that I just changed.

I will go to Files Upload. There we go. I'm going to upload this new customers.jmp. Now back in JMP. If we run this script again, take note of the old value we had here using the old data. If we run this again, we have about 3,000 less rows that were matched from that table that we had before. As you can see, with one click in the same script, we can get a fresh set of data without having to do any manual downloads or any manual joining of the tables that we have downloaded again. That's a very powerful feature that you cannot have without this data connector. It's a big reason why we really want people to use this to help augment their workflows.

Just to go through a few more examples of how these can be scripted, you can simply work with the data connector itself. You can get any of the values extracted out of these. You can also just simply open up Query Builder from these themselves and then build queries based on that. You can open multiple tables from a singular data connector. We've got the same OneDrive demo. I'm going to open Authors and Books out of this. That opened two new tables here.

We can open up Query Builder and do all sorts of different analysis based on the data with this. I've brought in two different tables: Fermentation Process and Fermentation Process Batch Yield Results. I've combined the temp and the tank level. This is all from that one script. This is very similar to what we had before. Then with this, we can pull it all from a SharePoint site and do the same thing with the data there.

I do want to emphasize that these connector configurations are one-time. Whenever you're coming through here, and you click New Connection, you go into the SharePoint site, you don't need to edit these every single time. Once you've got it configured and connected, you can reuse your connectors as you see fit.

One last thing before I wrap up the demo, a few more things is the SharePoint lists, briefly go over this. This is very similar. We have a Client ID, a Tenant ID, and then another site URL. This site URL is basically just the base URL of whatever list you want. I have a test list here. It's just that front part up until your email. This is all documented in the Marketplace documentation as well.

Then, if we connect to this, that takes us here. As you can see, I have my SharePoint Connector Test List, and we can open that up. As you can see, JMP will convert all of the different data types that are possible in this SharePoint list into types that JMP understands. Choices are converted to their text, and then locations are split out between different columns to allow you to do analysis based on all the information that's provided within those links. This can be a very powerful tool to analyze any data you may have in SharePoint lists as well.

One last thing before we wrap up our demo is I want to give a hint as to also what's coming in JMP 2027, and that is JMP Live refresh scripting. If you're unfamiliar with JMP Live, if you have a data table, you can go to File Publish, Publish Data to JMP Live, and then that will create a data table that can be viewed by anyone else with access to JMP Live that you have set up for it. You can actually use the refresh scripting feature that is available with this platform. You can start with that source script that I showed earlier that is generated from these tables that uses the New SQL Query.

This is still in active development, but just know that if you're a JMP Live user, and you have data on SharePoint, refresh scripting will be supported to come. There's also going to be more information about that with the next update. That is, once again, JMP 2027 only.

That is it for our demo. I'm going to go through, quick, frequently asked questions and some troubleshooting steps that you can use to help you with your connector connections. "What should I do when I try to log in and the browser says that the SharePoint and OneDrive data connectors app is not approved for use in my organization?" Like I said earlier, you can create your own authorization app on your Microsoft servers, but you can also use a built-in request link to communicate with your administrator about approving the use of the app. This works for quite a few people. But some organizations have data restriction policies that need everything to be self-hosted, so we provide those options for that reason.

You might need to approve the use of the app when you log in, because SAS may not be a verified publisher in your tenant, which is JMP, and we are hosting this app. Many times you need to provide that explicit access because of the permissions that are being requested from the app. Once again, I want to reiterate that that Tenant and Client ID is not required, and there's more information on how to set that up if you do need to use it.

"Does JMP and SAS access any of my company confidential data?" We want to reiterate that no, JMP does not access any company data. The authorization app that we provide simply provides the codes that say who you are, and you have access to what you're trying to gain access to. It is all in a closed feedback loop run locally on your machine, so there's nothing being processed on the JMP servers.

I want to round it out and go through these three key takeaways again. Now, hopefully you should be able to install and configure the SharePoint Data Connector, use it to create faster workflows using your SharePoint data, and you should also be able to understand common configuration issues and how to resolve them.

If you need any more information, you can always visit the JMP Marketplace listing for the add-in, which has lots of documentation for how to configure and set up the add-in for your purposes. Then I also have a blog post on the JMP Community, which goes into even more depth on the authorization options that we provide for this connector. Hopefully, there's an option that works for everybody, and you can get started using this connector to help augment your workflows in JMP. Thank you very much.