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Integrating Autodesk's Ecosystem into BIM Data Management: A Case Study on Enhanced Data Accessibility

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Description

Explore the transformative approach of integrating Autodesk data models with the AEC Data Model API and Data Exchange API into a new building information modeling (BIM) data management system. This case study will explore practical applications and strategies for using these powerful tools to centralize and enhance data accessibility within BIM projects. Discover how this integration not only simplifies data management, but also ensures that all stakeholders—from architects to engineers—have immediate access to critical data, thereby enhancing collaboration, accuracy, and efficiency in building projects. Through real-world examples, we'll demonstrate the steps and outcomes of adopting Autodesk's comprehensive data ecosystem, highlighting the seamless flow of information and its impact on project success.

Key Learnings

  • Learn about integration, and gain insights into how Autodesk data models can be integrated into a new BIM data management system.
  • Discover the advantages of centralized BIM data.
  • Examine case studies involving real-world applications of Autodesk's integrated systems.

Speaker

  • Andreas Bøving
    Andreas Bøving is the Product Manager for the Architecture, Engineering, and Construction (AEC) business at NTI, where he leads strategic decisions and product development for NTI's own products. With over 4 years of experience in developing innovative solutions, Andreas is a key player in driving the company's growth and success. He holds a Master of Science in Civil and Architectural Engineering and has furthered his expertise through courses in process leadership. This robust educational foundation, combined with his industry experience, allows Andreas to understand the complexities of the AEC industry and convert that knowledge into effective, supportive solutions. Andreas has been an active participant in numerous presentations and panel debates, most recently at DevCon 2024 in Munich, where he discussed NTI's use of Autodesk Platform Services (APS) and the Data Model API's.
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Transcript

ANDREAS BOVING: Hey, everybody. Thanks for joining this Autodesk University session. I'll talk about how we have integrated the Autodesk ecosystem into our new BIM data management system. This is a case study on enhanced data accessibility. My name is Andreas, and I'm a product manager at NTI.

So what are we going to talk about today? First off, just let you guys know me a little bit, who I am, and where I'm coming from. And then we're going to have a high level on the challenges we have in the AEC industry. We're going to talk about the data models from Autodesk, the AEC data model and the Data Exchange. We're going to have a practical walkthrough of how we have utilized it in-- how NTI Group has innovating with Autodesk Data models. And in the end, we have the future and some final notes.

So first off, about me, as I said, my name is Andreas. And I'm a product manager at NTI. I have the responsibility for the AEC line of business regarding our own IP. I have formerly actually educated as a carpenter and afterwards chose to take the education as a civil engineer, where I focused on energy and indoor climate.

And through this education, I actually started investigating how we could use the BIM models for much more than we are using today. And this way of thinking, it was something I took with me, started as an engineer at the large company called NIRAS, where I was the product manager-- sorry, the project manager for digitalization and showcased how the BIM module actually could be used for more specialist way of calculating the data and using the data in the models for special-- for different scenarios.

I'm located in Denmark and living in a small town with 50,000 citizens. At home, I have my partner and my two small girls. And in the free time, I'm trying to use it in the nature for hunting. Or otherwise, I'm actually ongoing a home renovation as we are speaking.

So NTI, some of you guys maybe know NTI, NTI Group. We have been expanding quite a bit in the last couple of years. Right now, we are actually almost 1,000 employees. And we are focusing both on the construction site, and then we have the design and manufacturing and the media and entertainment industries.

We have three pillars we are focusing on. So one thing is that, of course, we are Autodesk agents and we are Autodesk Platinum partners. Another big part of NTI is the consulting. We are trying to create the best solutions for our customers and help them in this rapidly growth of new ways of new softwares and new ways of working. And then we have this owner IP, where I am having my focus. And these three pillars is something that we can build these NTI solutions around, where we put our own software on top of Autodesk software to make sure that it fits the customer needs. And then we have the consultants to help you guys in implementing and using this.

As I said in the start, I'll try to jump in the helicopter and just take some sort of an high-level take on how I see the challenges is in the AEC industry. So first off, where are you coming from? And I know this is very basic, but maybe some of you actually experienced that you draw your project by hand. And that, of course, is needed for you to communicate what actually you need to build.

Then we saw that the 2D and the digital way of working was introduced into the industry and AutoCAD of course. And one thing is that it makes it easier for communicate and create more standardized way of communicating. But also, we started out this way make it more efficient in the projects. So we were able to produce more in the less time.

Then we are right now in a 3D area, where we are using a Revit, as an example. And that has opened up a lot of possibilities. One thing is, of course, that we are able to coordinate. Again, we have docs and pipes and all kind of disciplines. We need to make sure that they fit in these very, very complex projects we have today.

We also were able to be much more focused on the quantities. One thing is the areas, but also now the volumes that we are able to work with. And then, of course, visualization, so being able to see how will the project emerge when it's done.

And then I see that we are starting to emerge to the more BIM and data management area, where we will have much more focusing on data. And you will hear me say data lot of times in this presentation. I hope you bear with me because that is the new thing. We see the data will have a lot of different use cases.

One thing is that we are seeing that we are starting to work much more in the cloud. We are relying much more on the model data. And we are producing a lot more data than we usually did. And we expect that data is accessible for us to actually perform the necessary tasks we have in the project.

So from my point of view, what are the models mostly being used to today? So, as I said before, one thing is coordination and designing the projects. That is mainly part of why we're creating the models today.

And then we see that we are starting to using this model data for a lot of other scenarios. So we see that we are starting to try to calculate energy consumption based on the model. Again, extracting the data that is needed for these calculations. They can be areas as an example.

But that's just one scenario. We also see it for HVAC calculations, structure calculations, acoustic. There is many different scenarios where we are actually using and have to use geometry as a part of the calculation. And when we have these scenarios, that is where the model should be used and should be used more automatically.

And then we have seen that we the carbon footprint calculation. LCA is something that is very much top of mind for many people. Especially in the Scandinavian, we see that we have regulations that is introduced and that has caused that the models is need more data, need more detail levels, a greater detail level. And the we have to make sure that it's correct. So we align a lot on the models and what they are being used for us actually to produce these calculations.

Then we also see a lot of scattered data around in the project. We have many disciplines in a AEC project. We have architects. We have structural. We have electrical, all these kind of disciplines. They all provide some information to a project.

We see that we extract some of this information to what we call the documents, to Excel spreadsheets, to Word documents. And we are seeing that it is data that is crucial for us for design and for decision making. And we see that many of this data is placed in various places that is difficult to get to.

And we see that we are working maybe with old data because, again, we have all sorts of information throughout the project that hasn't been updated because it is exported and then it's just placed in a folder. And then maybe someone is taking that information, actually using it for their decision making. And that can cause some major errors.

We actually see that 35% of a project participant is using their time on non-productive activities-- sorry, project participant have 35 of that time on non-productive activities. And that is searching for the correct information, accessing the information. And this time should be used more wisely, and it should be used different.

Then I will try to give you guys an introduction to the data models. Some of you are, I assume, already knows what it is and what maybe they are capable of. I'll give you my take on how I see they will play in the industry and how I see they will solve many of the problems we actually have today.

So again, what is it solving? And we should always, when we are looking at new technologies, focusing on what is actually the problem. We should be more focusing on data and using the data and, again, utilizing data as a core part of a project.

I see that we have many barriers today. We should focusing on removing these barriers regarding accessing data and just working with the models. That can be time consuming, opening models as an example. And then, of course, we have just, as I said before, the access data is one of the main part of a time consuming task we have in a project. And it should just be something that we can expect that we have the correct data and we have easy access to data when we are working in a project.

We have this mission statement from Autodesk that Autodesk Data Models' mission is to unlock design and make data trapped within proprietary files by securely store storing, managing, and providing granular access so that the world can build faster, better and greener products. I'm totally supporting this mission. And I see that this is giving us a lot of potential and options to provide functionality to the industry.

So how do I see the data models will change the industry? I see that was our communication in the projects be much more fluent. We will have much easier access to the correct information. And because of that, we will have the same baseline of knowledge when we are communicating throughout the project team.

Then in collaboration, we will have a new ways to work together. We will have much easier access to the different disciplines' data in the project. One thing is that we have the Data Exchange APS. And that makes it possible for different disciplines in a project to exchange part of the model. And that makes it much easier and much more, what you call it, it's easier to access and easier to get the overview of the information, then instead of just getting a whole model with a lot of information.

And then we also see that this will make it easier for us. One thing is that we can work between different companies in the project. But also internally that we see that there are different disciplines. One thing is that maybe are designer sitting in the project and designing it, but we also see that the specialist that needs this information and maybe also want to enrich the objects with properties. Those two will have a lot easier to collaborate if they have easy access to each other data and the work they are doing.

Then we will see that we will have a lot of more focus on the BIM, of course, but also the data part of it. We will see that the model will be one thing, and the data and the properties will be another thing. So those two thing will be separated. And we will be able to easily and more agile working with the data and not necessarily opening large models.

We will also see a transition in how we see the projects. We will see that data will be located and assigned to a project. And the project owner will in many scenarios own this data. You will also see that instead of we have this small silos with models as small databases, all this will be able to combine and to find one single source of truth, where the data is for the project.

And we also see that already nowadays some ongoing investigations in the industry for how we standardize this. So it's easy to exchange. And it can live alongside the lifetime of a building. So when it needs to be renovated, then we have easy access to the old information that we actually produced through the designing process.

Then just some practical I'll just raise a flag. For one thing is the data models and the use and the different use cases, the IS. But the Autodesk guys have actually created a very nice playground for us. They have the Data Model Explorer and the Data Exchange Explorer.

And in these two explorers, then there you are able to actually try to see what information you can get through the different queries you can write. I am not a developer myself. But this is actually that easy that I can try out and see which data is accessible for me and have been a big part of how we were able to create our new product. So just a heads up.

Then I want to go a little practical on how we see the data models and how we, in NTI group, have been using them and have tried to create a new way of seeing data management. Before we started creating this as it was before, we have to focus on what are the problems in the industry. What is it we should aim to solve when we are creating this?

And we have three main areas. One thing is data accessibility. You have heard me mention it before in this presentation that there is a crucial part of a successful project that we have easy data accessibility and that the problems we hear out there in the street right now is it is troublesome to extract the model information. It is difficult to communicate without updated data. It is time consuming opening the models.

We also see that we have problems regarding insight into the model and project. And we hear problems like troublesome to get the needed project information. We are basing our decision on intuition and not correct information. We are actually lacking the information we should use for our decision making.

One other problem is the data quality. We hear that people are working with wrong or old data. We see that every project vary in quality. We see also we have scattered project information.

All these statements were something that we had a large, what you call it, survey around in the industry where we talked with various different players. And they all agreed on this is actually problems we have today in our projects. So that is what we have been trying to solve through this service.

So we created something called NTI CoManage. And that is utilizing many of the APSs. I have a small video I want to show you guys for how it looks like. So we can be, again, a little practical.

You should be aware that this is just got out of the oven. It's a brand new product. And it's still cooling on the counter.

But it is a cloud product focusing on data management and supporting the users to access and work with BIM data. I have this little small video will start afterwards. And in here I will just talk over, voice over it to explain you what it is, and what it can do.

Yes, so NTI CoManage is a project cloud product. So in here we can add projects and control the project data. So in the end here, I'm just adding a project. I'm giving it a necessary metadata. And then I can just add it.

Afterwards, I can go to my dashboard and see the projects I am a part of. So in here, I've just have an empty shell. So nothing set up right now. And then I navigate to what we call Sources. And here you can see I already have signed in to ACC. When I press Add source, we are going into the-- logging through the hubs. I, as a project participant, have access to and the project have access to and choose the different Revit models I want to have part of this project.

So now is the link connected. Now, I want to create the queries that we are using to extract the granular data we need for this project, again, the things that the AutoCAD Autodesk guys have been focusing on regarding creating these data model APIs. So I have set up which category I need for this specific source. And then I can start the synchronization.

So now we are actually extracting data directly from Autodesk Docs. Then I'm dropping a little clip here. And then you can see that we have successfully synchronized these four models.

So now we go into our configuration where we can set up which kind of data we need to work with. So I can create input parameters. I can create a model data, which is data directly from my sources. And I can create external data parameters that takes data from an external source. It could be an CSV file.

I can create parameters for type, objects. Or I can create parameters for instance objects. And, yeah, so here that just created some type parameters and some instance parameters. And I create some input parameters where I can write some notes. And I will create an approval parameter where it's just a yes/no checkbox I have in my list. All this can be set up as the project needs.

And then we can go back to CoManage. And in here, we see now that we have all the data that we synchronized before to the project. We have the viewer, which is an important part of this, that we want to make sure that the user that aren't in the model on a daily basis actually can get visual view of the model and the progress.

We have to make sure that when we see data in a table, like we have here, we should be able to locate where is the different objects actually in the model. So we can see here that I choose row. And then I can see in my model view where is this floor actually located. I can create these schemas as I want of views, as we call it. Now, I create a view called Rooms and will, of course only see instance objects because a room is an instance object.

Afterwards, I filter it. Right now we see all the instances that is in the project. So I filter based on the category, saying, I just want rooms, filter it. And afterwards choose which columns I want to add to this schema. So I say, OK, I want a Name and I want Room area because that is the data I'm interested in.

This data, I can then save the setting so I always have it to come back to. So when something updates, I have easy accessible-- it's easy access for me to see what have changed.

So this was just a tip of the iceberg presentation of the functionality we have. But it's showcasing how we are using the APS. Our vision with this is to elevate your projects by unlocking the full potential of BIM data. Our mission is to provide our customers with the tools to collaborate and combine that knowledge, remove unnecessary barriers, and allow data flow to construct the best possible project.

So how are we using the data models? Again, we have been focusing on, based on the whys you heard before, we have been focusing on aiming to solve our customer problems. And that is, as we heard before, the accessibility of data was one major problem they had. We know that the importance of these properties and the use of these properties is very important for the calculations they are trying to make.

Right now today, you have to have a person that actually is in the model and extracting the necessary information for you to perform these calculations. Again, anticipating that these two different persons in this scenario. So we are, of course, using the data models to extract this data so it is accessible for those who are creating these calculations, and they can be using it.

And we are actually enable the user to access and get the needed insight into these data. And by that, making sure they can quality assured, they can create standardized way of working with the projects. Again, this data quality is something that is very much focusing on, that we see the data models API-- or sorry, data model APIs actually is solving for us.

With CoManage, we see that we are starting to see the projects in three different areas. We have the models with our Revit models. It can be Civil 3D. It can be Plant 3D. And we have the designer in these models and working with the properties-- and sorry, working with the data and forming the project.

Then, of course, we have the file sharing that we is utilizing the Autodesk Construction Cloud Docs. One thing is file sharing. It can also just be file storing.

Then we have the property data. That is a quite new way of seeing the project that we also have this property data area where we have a different persona working. This is a persona that is a project manager. It can be a project leader. It can be a BIM manager. It can be a specialist.

This persona is not normally in the Revit model. But it needs this data and also needs the capabilities to actually enrich this objects with data that is specific for structure, color, behavior, or HVAC calculations. And that is where we see NTI CoManage try to fit in and make it-- creating a graphical user face for the user to actually utilizing these APSs, and again, of course, making sure that we try to see a single source of truth way of solving this data complexity we have in the projects.

Just to show you in a simple graph that we have Revit. And we can publish the Revit to our Autodesk Construction Cloud project to Docs. And when it's placed on Docs and we have been in to our Autodesk Construction Cloud hub, and that we want to use the data models APIs, we are able to browse to the Revit model from NTI CoManage and extract information. Right now, we have created a Revit add-in that makes it possible to push this data back to the model. But we know that Autodesk will provide functionality in the future that will make it possible for us to create a pure cloud solution.

We have the star here. And that's again just to showcase this is where the APS part of it. The data model, Data Exchange is making it possible for us to actually just work directly in the cloud.

One thing is that we will be able to push data back to the models through the cloud, through the ACC data model. We will also support multiple other products, like Civil 3D and Plant 3D. And that is opening up a broader spectrum of collaboration in large projects where you actually are working with Revit and Plant, as an example.

Just to highlight where we are using the APS services, we are using Viewer SDK in our viewer. And we have made it possible for the user to combine multiple models and place them on top of each other. Then we are using the Data Management API for accessing these data in the customer's ACC. And we are using the Data manager API because we want to make sure we can support both the ACC Data Model and the Data Exchange API.

I know that the ACC Data Model and the Data Exchange API actually have ways of, what to call it, access these models through the user's project-- access these models placed on the users projects. But again, the Data Management API makes it possible for us to combine these model in one place when you have to browse through them.

We also using the Data Management API to see if there is any updates on the users projects. So in this scenario, you can see on the screenshot here that we actually have a model that is having an update available. So now I know, as a user, I should update my data to make sure I have the newest information to use as base for my decision making.

Then, as I said, we have these settings where set up which information I actually want extracted from my Revit files. And again, this is a sort of a graphical way for a non-developer type. So in here, I can just see the different categories I have in my Revit model. And I can choose which one is I'm interested in.

Behind the scenes, you can see we have this just a, what you call it, the query we use right now. We have multiple queries we are running. But just to give you an idea of how it looks like, Autodesk have chosen to support the GraphQL way of query data. And it's very strong and is giving us a lot of capabilities of extracting exactly what we need. So, yeah.

Then we have the future. And it's more like how we see the future. So I have these-- keep that in mind.

Some of the possible changes I think that will happen in the AEC industry, not tomorrow, but years ahead. We will go towards a more fileless way of working. We will see many of these, what you call it, events and processes which they rely on Revit files. And as an example, you will see that we will go towards more cloud based. And we will see that we will use APIs both for enriching the models, but also for designing the models.

We will see that the models will have a more focus on what they actually should. So again, models, you're focusing on being the best way of coordinate and visualize the project. So again, should not be used for small databases. It should just be focusing on what they do best.

And then, we will probably see that a object in a model will have a direct connection to the cloud. So we will probably see that all the properties we today have in the models will be extracted and placed in the cloud instead. For one thing is to make the models easier to work with because of the file size, but accessibility and able to create a combination of different-- so if you have a doll, for example, you want to have a direct link to a producer of that doll. And being able to do all this in the cloud, instead of having to open a Revit model and editing these properties. I just think that this is something we're going to see in the near future actually that those two ways-- that way of working will happen.

We also see that there is a lot of these common data environments. And we need and we will also see that the data should flow easily between those OCDs. And again, we see that we will support the project's the way of working. So if the project needs to use those specific sorts of software, we will be able to work together unlimited and make sure that we create the best possible project.

Final notes-- so unlocking the future of data management in AEC, just sum up all the things I have said. So what is the challenges right now? Data accessibility, scattered information, and inefficient workflows.

What do I see the key benefits that the data model will give us is NTI CoManage is an example of what we actually are capable of doing with these new technologies. And I think the DMs will participate in solving many of the challenges we have today.

Then, of course, I have a vision for the future. I see that we will be much more data driven. We will work without files. We will have a Cloud Workflow instead.

We will go away from all these silos. And we will focus more on the project as a team, and not so much on the company or the product you're using, but on the project and making sure to create the best possible project we can. And again, because of the data flow, we will be able to support, I think, that is actually possible for us to do.

And then, of course, there's finally, a call to action. I hope you guys have been inspired by this and will work more data driven and also challenge this is how we are used to do it statement you probably hear out there. I think one thing is the existing APS services there are can give the tools you need to extend your toolbox. And hopefully, I see that we, in the AEC industry, will work in much more data oriented in the near future.

Thanks for watching my presentation and have a very good day.

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We use Commission Factory to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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