Trending March 2024 # Get Data From Onedrive Or Sharepoint With Power Query # Suggested April 2024 # Top 10 Popular

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Nowadays many of us are saving our files to the cloud using OneDrive for Business or SharePoint Online. Unfortunately, it’s not straight forward to get data form OneDrive or SharePoint with Power Query, so in this tutorial I’m going to step you through the three scenarios: getting data from an individual file on OneDrive or SharePoint, getting data from a SharePoint folder, and getting data from a SharePoint shared library.

Note: The SharePoint Folder connector is only available in Excel 2023 Professional Plus and with a Microsoft 365 Apps for Enterprise license.

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Get Data from a Single File on OneDrive or SharePoint with Power Query

I’ll start with getting data from an individual file on OneDrive or SharePoint. Either way the process is the same and it requires getting the file path, but not the file path as you know it.

If you’re like me, you’ll have your OneDrive files synced to your hard drive. You can see mine here in the file explorer:

If you try to copy a file’s path from here it will reference the copy of the file on your hard drive, not the OneDrive/SharePoint file path.

The trick is to go to OneDrive or SharePoint online and open the file from there in the Desktop App:

Now that you have the file path you can close the file and create a query in a new Excel workbook using the From Web connector in Power BI or Excel (shown below):

Paste the URL for the file into the dialog box, deleting the ?web=1 from the end before pressing OK:

At the authentication dialog box choose Organizational Account and enter your OneDrive or SharePoint logon credentials:

Get Data from a Folder on OneDrive or SharePoint with Power Query

Getting data from a folder on OneDrive or SharePoint requires a different approach. First, we need the folder path, which you get from your browser. In the image below I want to get data from the folder called pq_2.05_excel_workbooks:

I simply copy the portion of the URL up to _layouts/15…, which you can see highlighted in pink.

Then in Power BI or Excel (shown below) you want the From SharePoint Folder connector:

Paste in the URL and at the authentication dialog box choose Microsoft Account and sign in with your SharePoint logon credentials:

Training/Training Content/ Syllabuses MOTH/Excel/Power Query/Lessons/Practice Files/pq_2.05_excel_workbooks:

IMPORTANT: remember Power Query is case sensitive, so you must enter the folder path exactly as it appears in SharePoint.

IMPORTANT: the sheet or table that you choose must have the same name in each file you want to consolidate.

This will consolidate the data in each file into one table and from there you can perform further transformations.

Get Data from a Shared Library on SharePoint with Power Query

Lastly, if you work with Shared Libraries in SharePoint Online then the process is a hybrid of the first and second examples. You can see in the screenshot below that I’m in our My Online Training Hub Team Site and I want to get the data from the Example Data folder. You can see it’s a Shared Library from the list on the left.

There are two ways you can get the URL for the shared library, one is to copy the domain from the URL, but you need to remove the -my from the URL before pasting it into Power Query.

Alternatively, if you open one of the files in the folder in the desktop app…

You’ll notice the URL you get through this path does not include ‘-my’ so it’s ready to use by selecting the path up to and including chúng tôi e.g.:

Then in Power BI or Excel (shown below) you want the From SharePoint Folder connector:

And the process from here is the same as the previous example.

Sharing Files with Power Query Connections to OneDrive or SharePoint

If you want to share files with other users you need to make sure they have permission to access the file, folder or shared library.

Then in Power Query they’ll also need to enter their credentials. Power Query will prompt them to edit their credentials when they open the query editor. As shown below where you can see a yellow warning bar below the ribbon. Alternatively they can edit them via the Data Source Settings on the Home tab.

Select the source from the list

Edit Permissions

Edit to switch to a different account


Big thanks to fellow Microsoft MVP, Wyn Hopkins for demystifying connecting to OneDrive or SharePoint in his video here.

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Power Query Custom Data Types

You may already be familiar with Excel Data Types for geography and stocks, but with Power Query Custom Data types we can now create data types based on our own data.

This enables us to organise our data into a single column and then extract and reference the underlying columns/fields using formulas.

It’s a streamlined way to manage and consume your data enabling you to create interactive reports like the one below:

Note: Power Query Custom Data Types are currently in preview on the Beta channel for Microsoft 365 Windows users, however only 50% of Beta channel users will have received this new feature. I just happened to be in the lucky 50%! When the feature is generally available it may be restricted to a specific licence, but I don’t have details on that yet.

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How to Create Power Query Custom Data Types

In this example I’m going to get some data from the web for 2023 Tour de France from this URL:

Tip: before you create your data type, use the filters to remove any unwanted data, rename any columns as necessary and set the data types for each column e.g. dates, text, numbers etc.

Step 5: Give your data type a name and choose which column you want displayed

Step 6: Rename the query if required and Close & Load to a Table

Tip: the query name will be the name of your Table when it’s loaded to the Excel sheet and you’ll use this name when referencing the data, so make sure it’s something useful.

Note: the beauty of the data types is that you don’t need the columns displayed in the table to work with them (unless you want to use them in a PivotTable). With Data Types you can reference the fields in formulas:

Power Query Custom Data Types Limitations

There’s currently no support for images.


You can only build a PivotTable from fields visible in the table.


Values with a Data Type icon are not the same as text, as you can see in the image below when I compare the data in cells D2 and E2 to the rider value in A2. However, we can convert data types to text using the new VALUETOTEXT function as you can see in cell D6:

This is useful when looking up text values in data type columns. e.g.


And in the Conditional Formatting in my example file:

Another function designed to work with data types is ARRAYTOTEXT, which converts the array to a comma delimited string of values.


COUNTIF/S, SUMIF/S etc, cannot handle the array returned by Riders[Rider].Team e.g. this formula will not work because COUNTIF requires a range in the first argument:


However, this equivalent of the COUNTIF formula using SUM and Boolean logic will work because SUM can handle an array:


The point being that some functions can handle the arrays returned from data types and some can’t. You can use workarounds like the alternate SUM formula, or you can perform the calculation in two steps; 1. return the data to cells and then 2. reference those cells in your formulas. E.g. =COUNTIF(K4#,C3.Team) where K4# is the range returned by =Riders[Rider].Team as shown below:

Not so much a limitation, but you’d think with only one column of data occupying cells in the worksheet that the file size would be smaller than if all the columns were visible. However, in my experiments the file containing the data type was slightly bigger than all the data stored in a regular table without a data type. So, while data types won’t reduce your file size, they sure make your workbooks less cluttered.

Sharepoint Benefits In Power Bi Report Development

I want to talk about the three main benefits of SharePoint. We’ll talk about the three overarching benefits and go into detail as to what those benefits mean and how the features of SharePoint enable those benefits to occur. You can watch the full video of this tutorial at the bottom of this blog.

The first of the SharePoint benefits is what I like to call content management and delivery. This area has always been a key problem in workplaces all around the world.

It is estimated that about 30% of your time is spent sending, replying, and organizing emails and data. SharePoint can help your employees and yourself get some of that time back.

By the way, that’s about 2.6 to 3 hours a day that you could potentially get back with SharePoint. People use SharePoint to store documents similar to how they do it for OneDrive. But the benefit with storing your documents with SharePoint is you can attach metadata to each document.

For example, let’s say you have an accounting folder where you have all your files separated by year first and then by the actual account itself.

Now that’s a very complicated system, especially if you want to see all the files for a certain person, right? All the files for a certain person, or all the tax files for every year are located in different folders so it’s hard to do that in a traditional OneDrive or desktop format.

So what SharePoint has done is to create document libraries, where all of your files are in a list and you can attach metadata to your documents.

In our example, we have a metadata called Year, another metadata called Account Type, and another metadata called Person.

If you want to look at all of the files for a specific person, you can just go over to that metadata and filter to that person. You would see all of the files for all of the years. If you want to go back to the original way and just look at all the files for a certain year, then you would go over to that metadata and filter to that year.

Metadata is the next level of organization for your document library.

I’m so surprised that not more companies do this. When they do this, they see improved productivity in finding the documents that they need.

This is also very scalable. For example, you could have a document library for your contracts, another document library for your accounting, and another document library for your HR. They can be held separately so that someone in HR cannot review the documents in accounting.

Another feature that allows for robust content management delivery is through SharePoint lists. In this example, we have a customized database that someone has created to hold the data that is relevant to them.

This is a list of event itineraries. Each record here is a specific event in that event itinerary. We have a Breakfast meet & greet Welcome & Introduction, and so on.

What this person has done is to create columns that are relevant to them. So for each session, they have a code, type, description, speakers, start time, and end time.

What’s powerful about SharePoint lists is that they give you the versatility of a robust database, and they are easy for a worker to actually employ. It’s very easy to create your own list and column types. You can have sophisticated column types like choice columns (eg. Session type) or user-based columns (eg. Speakers).

There are many things you can do once your SharePoint list has been created. It’s also scalable because you can create one for many things. You can create one for expenses instead of doing it in a random Excel file that’s very hard to access. Everyone can access and update it. If there are changes, you can require approvals for those changes and add tiny workflows.

These lists can be modified with attachments as well. For example, this is a list of blog articles where each one is an actual file. So this is a mix of document libraries and SharePoint lists, where someone’s created a document library with metadata and columns from a SharePoint list.

So you can do a lot of mix and match here too. This is much better than your data being in some random warehouse or OneDrive or emails.

SharePoint is an all-in-one place for all your data, whether it’s a document library or a SharePoint list.

The final feature for SharePoint is that it is a team site. It’s an internal team site where all your employees can access the information they need. You can have a team site for your entire organization for things like news, blog posts, calendars, quick links, and external resources that your employees use.

For example, if I want to find my HR policies, I don’t have to email the HR person. I can go to the team site and find the HR section to find all the documents that I need.

It’s also really relevant that when you have SharePoint, your organization’s team site is your homepage. So as soon as someone opens up Chrome or Explorer, they can see the latest company news and activities.

You can have group-specific team sites as well. You can have one team site for the entire organization and another team site that’s private for your team so that only information that’s relevant to the employee is given to them.

You can create your own SharePoint sites and SharePoint lists. It’s very easy for anyone to create it since there’s no coding involved and it’s all drag and drop.

One of the important SharePoint benefits concerns business process workflows. This is an example of a very simple business process workflow for an organization.

A piece of document arrives to an email inbox, which is rerouted to reviewers. It then goes through multiple stages of reviewers. If they approve, it’s accepted; if not, it’s rejected.

This process involves a couple of emails, right? You have an email arriving to the actual inbox. Then an email has to be sent to Anna and Sean to review. Anna and Sean will probably email each other to review it. And then finally another email to indicate approval or disapproval.

Now, if the data that is used is actually within SharePoint, this workflow can be automated. For example, we can create a SharePoint list that has all of these documents. The document arrives and it needs to be reviewed by either Sean or Anna before it’s accepted.

Instead of an email process, the person who wants the approval can upload it into a SharePoint list or a document library, which then automatically sends an email notification to Sean and Anna. This can be done through either Power Automate or SharePoint’s internal workflow system.

We’ve actually done an expense approval system on our YouTube series, where we talked about how to use Power Automate with SharePoint to automate that system.

Here’s a simple expense approval that I did for an organization, which previously used to take about 7 or 8 emails and had way too many pain points. Previously, the employee who submitted the expenses was kept out of the loop, and there was no way to organize everything afterwards.

SharePoint and a workflow system like Power Automate can really fix this. Once you have your data, processes, and SharePoint, it’s very easy for other apps to come in and improve that process.

We’ve talked about how SharePoint and Power Automate can be used to automate business process workflows. But the same thing can be said with SharePoint and Power Apps. Let’s say you don’t want Sean and Anna to access SharePoint at all.

You can create an app for Sean and Anna where they can go on a website that shows them the contracts that they need to review one by one. They don’t get any emails, they just log onto the app. And again, the best thing about Power Apps is that it’s no code.

SharePoint is also very powerful with Power BI. For example, let’s say you have your expense approval system in SharePoint. That also means you’re tracking all the data for that process. You’re tracking who submits expenses, how much they are, and how long it takes to review everything. One of the SharePoint benefits is that you can use the data to create a report and a dashboard on Power BI.

SharePoint enables workflows, but integrating it with other Power Platform apps really takes it to the next level.

The third of the SharePoint benefits is collaboration. This is one of the reasons why most organizations justify purchasing SharePoint to improve their productivity. There are lots of SharePoint benefits and features that enable a collaborative environment. I’ll go through each one very quickly.

Version control allows you to make sure your documents are up to date and if there are any changes made to documents, you can always go back to the previous version.

Approve and review is like what we talked about in the business process workflows. You can have a document library system set up where someone submits a document and someone else needs to approve or reject that document.

All-in-one bank is a philosophy where all your organization’s information should be in one place. So it should not be repeatable and easily findable for anyone who needs to find it.

Extensions can be created within SharePoint and imported to improve your collaboration. Things like task tracker, widgets, and Kanban boards are something that’s heavily used within SharePoint pages to improve collaboration.

Permissions allow you to select certain groups of people to have access to information. Sometimes, companies suffer from information overload. You don’t want everyone to have access to everything, and if you have very sensitive data, you need to make sure that only the people you want to see it actually see it.

Scalability is another great benefit. If you don’t do SharePoint on-premises but you do SharePoint on the cloud, you can scale up from 10 people all the way to a million people in a Microsoft server. It’s very easy to employ and you only have to play a flat rate per person.

Strong integration with Office 365 is also there since it’s made by the same parent company, Microsoft. If you have files in Excel, Word, or PowerPoint, you can actually edit them online in SharePoint rather than downloading them and editing them.

In this post, we discussed the three key SharePoint benefits. We talked about how SharePoint is very good at content management, business process workflows, and collaboration.


Boon From Big Data Or Loss Of Privacy?

Today’s post is going to be different.

There is no technical subject matter I am going to talk about. But the article is far more thought provoking than any of the article I have written till date.

[stextbox id = “section”] A real life incident:[/stextbox]

Let me start with a real life example to get your thinking process started:

About 6 months back, I bought a top end Android smartphone. After using it for a month or so, I accidently started Google Now on the phone. The interface looked very simple on first look (nothing more than a search bar and weather update). So I moved back from the application and started living my usual life.

I would have almost forgot this instance like multiple other applications which come with the phone and I don’t use. However, Google had something else in store. A week after I opened the application for first time, I got a notification on my home screen, suggesting that I am 15 minutes away from Home and the traffic on route is normal!

The notification took me by surprise. I never told my phone where my home is! Over the next few days, the application identified my Office, commute place, friends place, the websites I visit frequently. It now integrates my searches across devices. So if I search a restaurant on my laptop, my phone shows me the route to same restaurant!

The incident above is like a dream come true for a lot of analysts and a scary incident leading to loss of privacy to a lot of customers.

As an analyst and some one who specializes in predictive modeling, I am usually a proponent of big data and the changes it is bringing to our day to day life. However, I have to admit that Google took me by surprise and has made me think and reflect a lot more on how life is changing. It has ensued a debate between 2 sides of my personality.

[stextbox id = “section”]Two sides of debate:[/stextbox]

My first personality is that of a common man. I want my privacy, specially during some personal moments. These moments could be the time I spend with my family or when I am reading or may be talking to a friend. I don’t want interruptions or suggestions from any third party during this period. I want to relish the moment as it is. After going through the experience mentioned above and many more like that, I am not sure whether these moments will remain as pristine and unadulterated as I would want them. Would my reading experience be marred by suggestions about different things I might like? Would the phones pop up notifications about my friend when I am talking to them? or may be when I am talking about them to my wife? The possibilities are limitless!

The other side of my personality is a big proponent of technology and Analytics. I remain excited about how technology can be used to solve day to day problems. I come out with innovative ways of using data to create value (for customers as well as Organizations). I continuously think how behavioural modeling can help customers in breezing through day to day chores? How can I predict something before it actually happens.

[stextbox id = “section”]How do we resolve this?[/stextbox]

The second personality needs to be cognizant about the presence of first personality and take actions which are in sync with values of first personality. Here are some rules I have come out with, which every analyst needs to keep in mind while designing a product or working on his next big data project:

[stextbox id = “section”]1. Transparency:[/stextbox]

This is the biggest takeaway. The bare minimum an analyst needs to make sure is that the customer is aware about what data is being collected and how can this be used. This needs to come out clearly. This is similar to apps (on smartphones) asking permissions before installing them. If you are collecting data with out asking customer explicitly, you are headed for disaster.

So, instead of using data through a pre-selected tick box (buried somewhere is my phone settings), I would have appreciated if the app reminded me of the data it will use, when I started it for the first time.

[stextbox id = “section”]2. Develop a character of your Organization by keeping customer at the heart:[/stextbox]

Let me try and explain. Years before Google started collecting information about usage from Android phones, Microsoft started this for MS Office. They asked me whether I would want to share my usage patterns with Microsoft, which will help them improve user experience further. I almost always declined. When Google asks me same thing, I am more open to sharing information.

It might be a personal choice. However, the reality is that I am more open to sharing data with Google because I can relate to the benefits they have provided me by using this information. I have benefited by sharing some of this information with Google.

The message is that if you don’t provide the benefit of this information back to the consumer, they will stop sharing this information.

[stextbox id = “section”]3. Make change in subtle manner:[/stextbox]

Big changes in user interface or the way new product gets rolled out can take customer by surprise. You have to build in these changes in subtle manner. In a way such that the customer still feels as much at home as possible. I think Google does a nice job at it. Here are some best practices:

Provide an option to user to switch back to old proposition, if it is not working for him

Try and keep as much user interface unchanged as possible.

[stextbox id = “section”]4. Test and roll-out:[/stextbox]

Irrespective of how good an idea is, you should avoid making complete roll-outs without testing. There are multiple benefits from this:

You actually act based on how customer feels about the product

You can size the benefit / loss you have seen by moving to a new product.

I think until and unless Organizations and analysts adhere to these rules, it might only be a question of time before they face a bunch of disgruntled customers.

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Power Bi Copilot: Enhancing Data Analysis With Ai Integration

Are you ready to elevate your data analysis capabilities? Then let’s delve into the realm of Power BI Copilot and its AI integration. This tool isn’t just another addition to your data analysis toolkit; it’s akin to having an intelligent assistant, always ready to help you navigate through your data.

In this article, we’ll explain how Power BI Copilot works and how you can leverage it to empower you and your organization.

Let’s get started!

Copilot is an AI tool that provides suggestions for code completion. The tool is powered by Codex, an AI system developed by OpenAI that can generate code from a user’s natural language prompts.

Copilot already has Git integration in GitHub Codespaces, where it can be used as a tool for writing tests, fixing bugs, and autocompleting snippets from plain English prompts like “Create a function that checks the time” or “Sort the following information into an alphabetical list.”

The addition of Copilot in Power BI has infused the power of large language models into Power BI. Generative AI can help users get more out of their data. All you have to do is describe the visuals or the insights you want, and Copilot will do the rest.

With Copilot, you can:

Create and tailor Power BI reports and gain insights in minutes

Generate and refine DAX calculations

Ask questions about your data

Create narrative summaries

All of the above can be done using conversational language. Power BI already had some AI features, such as the quick measure suggestions that help you come up with DAX measures using natural language, but Copilot takes it to the next level.

With Copilot, you can say goodbye to the tedious and time-consuming task of sifting through data and hello to instant, actionable insights. It’s the ultimate assistant for uncovering and sharing insights faster than ever before.

Some of its key features include:

Automated report generation: Copilot can automatically generate well-designed dashboards, data narratives, and interactive elements, reducing manual report creation time and effort.

Conversational language interface: You can describe your data requests and queries using simple, conversational language, making it easier to interact with your data and obtain insights.

Real-time analytics: Power BI users can harness Copilot’s real-time analytics capabilities to visualize data and respond quickly to changes and trends.

Alright, now that we’ve gone over some of the key features of Power BI Copilot, let’s go over how it can benefit your workflow in the next section.

Looking at Power BI Copilot’s key features, it’s easy to see how the tool has the potential to enhance your data analysis experience and business decision-making process.

Some benefits include:

Faster insights: With the help of generative AI, Copilot allows you to quickly uncover valuable insights from your data, saving time and resources.

Ease of use: The conversational language interface makes it easy for business users with varying levels of technical expertise to interact effectively with the data.

Reduced time to market: Using Copilot in Power Automate can reduce the time to develop workflows and increase your organization’s efficiency.

Using Power BI Copilot’s features in your production environments will enable you to uncover meaningful insights from your data more efficiently and make well-informed decisions for your organization. However, the product is not without its limitations, as you’ll see in the next section.

Copilot for Microsoft Power BI is a new product that was announced together with Microsoft Fabric in May 2023. However, it’s still in private preview mode and hasn’t yet been released to the public. There is no official public release date, but it’ll likely be launched before 2024.

Some other limitations of Copilot include:

Quality of suggestions: Copilot is trained in all programming languages available on public repositories. However, the quality of the suggestions may depend on the volume of the available training dataset for that language. Suggestions for niche programming languages (APL, Erlang, Haskell, etc.) won’t be as good as those of popular languages like Python, Java, C++, etc.

Doesn’t understand context like a human: While the AI has been trained to understand context, it is still not as capable as a human developer in fully understanding the high-level objectives of a complex project. It may fail to provide appropriate suggestions in some complicated scenarios.

Lack of creative problem solving: Unlike a human developer, the tool cannot come up with innovative solutions or creatively solve problems. It can only suggest code based on what it has been trained on.

Possible legal and licensing issues: As Copilot uses code snippets from open-source projects, there are questions about the legal implications of using these snippets in commercial projects, especially if the original code was under a license that required derivative works to be open source as well.

Inefficient for large codebases: The tool is not optimized for navigating and understanding large codebases. It’s most effective at suggesting code for small tasks.

While Power BI Copilot offers a compelling platform for data analytics and visualization, its limitations shouldn’t be overlooked. You have to balance the undeniable benefits of Copilot with its constraints and align the tool with your unique operational needs.

As we mentioned in the previous section, Copilot for Power BI was announced at the same time as Microsoft Fabric, so naturally, there’s a lot of confusion about whether Fabric is replacing Power BI or whether Power BI is now a Microsoft Fabric product.

Microsoft Fabric is a unified data foundation that’s bringing together several data analysis tools under one umbrella. It’s not replacing Power BI; instead, it’s meant to enhance your Power BI experience.

Power BI is now one of the main products available under the Microsoft Fabric tenant setting. Some other components that fall under the Fabric umbrella include:

Data Factory: This component brings together the best of Power Query and Azure Data Factory. With Data Factory, you can integrate your data pipelines right inside Fabric and access a variety of data estates.

Synapse Data Engineering: Synapse-powered data engineering gives data professionals an easy way to collaborate on projects that involve data science, business intelligence, data integration, and data warehousing.

Synapse Data Science: Synapse Data Science is designed for data scientists and other data professionals who work with large data models and want industry-leading SQL performance. It brings machine-learning tools, collaborative code authoring, and low-code tools to Fabric.

Synapse Data Warehousing: For data warehousing professionals, Synapse Data Warehouse brings the next-gen of data warehousing capabilities to Fabric with open data formats, cross-querying, and automatic scaling.

Synapse Real-Time Analytics: This component simplifies data integration for large organizations and enables business users to gain quick access to data insights through auto-generated visualizations and automatic data streaming, partitioning, and indexing.

OneLake: The “OneDrive for data,” OneLake is a multi-cloud data lake where you can store all an organization’s data. It’s a lake-centric SaaS solution with universal compute capacities to enable multiple developer collaboration.

Through Fabric, Microsoft is bringing the capabilities of machine learning models to its most popular data science tools. There are other components, like Data Activator, which are still in private preview and are not yet available in Fabric.

Microsoft Fabric is available to all Power BI Premium users with a free 60-day trial. To get started, go to the Power BI admin portal and opt-in to start the free trial.

In a world brimming with data, Copilot might just be the ‘wingman’ you need to make your data speak volumes. It’s turning Power BI into a human-centered analytics product that enables both data engineers and non-technical users to explore data using AI models.

Whether you’re a small business trying to make sense of customer data or a multinational figuring out global trends, give Copilot a whirl and let it take your data analysis to the next level. Happy analyzing!

To learn more about how to use Power BI with ChatGPT to supercharge your organization’s reports, check out the playlist below:

Copilot in Power BI is still in private preview, but it will become available to Power BI customers soon. With this tool, users can use natural language queries to write DAX formulas, auto-generate complete reports using Power BI data, and add visualizations to existing reports.

To use Copilot in Power BI, all you have to do is write a question or request describing what you want, such as “Help me build a report summarizing the profile of customers who have visited our homepage.” If you want Copilot to give you suggestions, type “/” in the query box.

Once Copilot for Power BI comes out of private preview, it’ll be available at no extra cost to all Power BI license holders (pro or premium).

Arria Nlg: Connecting The Data World With The Power Of Language

Arria NLG has a unique approach towards the deployment of NLG. As there are so many markets and use cases where NLG can and will offer a huge value-addition, Arria NLG’s software design allows its customers to decide on where to implement NLG to meet their goals and challenges. The company’s “Studio” solution which can be deployed as a SaaS and on-premise solution has been designed for users within an organization to write and deploy their own narratives. Studio is supported by their SDK and also with the Microservices available on their NLG marketplace store. Arria also has a professional services division to help clients with their implementation.

The Foundation of Arria NLG

Arria NLG was set up to enable the use of NLG and was inspired by the history of the founders of the University of Aberdeen and their dedication to language. Arria’s mission is to democratize NLG technology making it easily available to everyone, everywhere. Arria’s journey dates back to 1495 when the University of Aberdeen was founded with a focus on language and the pursuit of truth in the service of others. Bishop Elphinstone believed in the Power of Language as we do today. His beliefs are what led to the creation of Natural Language Generation technology.

It was not until 2009 that the University identified the global potential of the breakthrough of their NLG software technologies and finally in 2013 commercialized the technology as we know it today, Arria NLG. The company brings the power of language to data, big data technology,and AI. At Arria, they are not just building a global commercial enterprise, but a scientific legacy.

About the Team

Stuart Petersen is the Chief Strategy Officer at Arria. The company is led by Co-Founder, Chair and CEO, Sharon Daniels as well as two leading experts in NLG technology, Chief Scientists and co-founders, Dr. Ehud Reiter and Dr. Yaji Sripada. Sharon has decades of experience in developing and implementing technology within global enterprises. Her background in business strategy, technology, and how to implement new transformative technical capabilities within complex commercial settings allows Arria NLG to meet and exceed its growth targets. Sharon is recognized globally as an industry leader. Notably, Sharon was also co-founder of Diligent Corporation which was acquired in May 2024 for US$624 million

Strong Leadership Position with Global Recognition

Arria’s patent portfolio protects its proprietary articulative analytic techniques and NLG Technologies. With these 13 core NLG patents (and many more pending), Arria maintains its commanding position in the NLG marketplace. This patent achievement allows Arria to maintain sole ownership of its core differentiators with the strength and scalability of pure computational linguistics. In addition, the technology suite ensures everyone has an NLG solution to fit their specific skill sets and needs (STUDIO, SDK and Microservices).

In 2023, Arria won the Best Innovation in NLP category at the Alconics awards, the world’s only independently-judged awards celebrating Artificial Intelligence for Business, which were announced at the AI Summit in London.

Also, in 2023, one of Arria’s customers, Urbs media in conjunction with the Press Association, received a 706k EURO grant from Google to fund its local news automation service (which is powered by Arria’s STUDIO technology). This is one of the largest grant allocated from Google’s Digital News Initiative (DNI) to date, which is focused on stimulating and supporting innovation in digital journalism across Europe.

Customer-Centric Solutions

Arria NLG offers a unique approach of providing solutions and services that directly give a user the power to cleanly and consistently capture and deploy human expertise and insight directly from the heart of the data, all in real-time. The company believes that the technology will really push big data even further into the mainstream.

Arria NLG does not know all the use cases where NLG can be deployed because when we look at everyday life, we can see so many areas and use cases where NLG can be deployed for the immense benefit to both people and business.

Challenges Executed by Arria NLG

Arria NLG’s story has been the traditional technology company in a technology paradigm that has been in its infancy, irrespective of how good that technology is and is now moving into the core adoption phase. Even though NLG has been around for some time now, the growth of big data and NLP (Natural Language Processing) has been the enabler for NLG to become embraced by businesses at scale. Arria feels that we are now at that adoption and growth phase of NLG.

NLG is an area where there are so many potential use cases within different industries such that a company can get lost in trying to meet all the requests coming in from these areas. Successful companies analyze, focus and execute on where there is the coalescence of repeatable opportunities with a large potential market audience and the application being able to meet those needs. At Arria, the company has striven to focus on where they believe the best markets and use cases are and stay focused on them.

Insights into the Future

The company foresee a huge adoption of NLG across many markets and use cases and the ones that we had not even thought were possible. NLG is being co-mingled with NLP to drive what is now being called “Augmented Analytics”. As Arria is providing “Studio” solution to their clients so that they have the ability themselves to build NLG into the core fabric of their business, the company truly believes that we have only started to scratch the importance of NLG and Arria is perfectly positioned to become the pervasive solution to one of the most pervasive technologies for many years to come.

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