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Unlocking Autodesk Platform Services Insights: Data Visualization for Strategic Decision Making with Insights

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Descripción

This session will showcase the transformative power of Autodesk Platform Services visualization capacity, demonstrating how to convert complex scheduling data into actionable insights. Participants will explore various visualization techniques and tools that can help reveal underlying trends and operational bottlenecks. By harnessing these insights, attendees will learn how to proactively address challenges and unlock a powerful set of possibilities for efficiency and optimization in project management and operations. The session will include hands-on examples and real-world case studies, showcasing how Autodesk Platform Services data can be used to drive strategic decisions and foster innovation in planning processes. The class will also encompass the journey of data and creating bridges for easy interpretation using Autodesk Platform Services. This class will help participants learn from real-life data, examples, and solutions to real-life problems using insights.

Aprendizajes clave

  • Learn about specializing in Autodesk Platform Services data visualization techniques with insights for clarity and innovation.
  • Explore case studies where data insights have transformed planning strategies.
  • Learn how to use real-time data to improve decision making and project outcomes.

Oradores

  • Avatar para Enrique Galicia Tovar
    Enrique Galicia Tovar
    With 17 years of expertise in Building Information Modeling (BIM), I currently lead as the Director of Innovations and AI, specializing in developing cutting-edge solutions that streamline workflows and enhance interoperability across various platforms. Leveraging a deep knowledge of software development, I craft customized tools in C#, Python, and JavaScript, primarily utilizing Autodesk Revit, Navisworks, Dynamo, and Autodesk Platform Services. I consult internationally, delivering BIM software development solutions that address complex challenges within the industry. My role involves transforming theoretical concepts into practical, scalable applications that propel technological advancements in architectural and engineering contexts. Beyond technical development, I am passionate about education and knowledge sharing. I have created over 100 online courses that cultivate skills in BIM technologies, benefiting 30,000+ students globally. These courses collectively contribute an impressive 10 hours of learning daily, underscoring my commitment to expanding the capabilities of future professionals in the technology and AI domains.
  • Ravi Wood
    Ravi Ray Wood is an Expert BIM Manager in Architecture with projects across USA, Canada, Europe, Middle East, Singapore and India. He specializes in BIM execution and implementation across large scale projects including Infrastructure, Residential, Hospitals, Commercial and Retail. His astute acumen and proven track record in handling large teams to optimize resources and successful deliver BIM projects has helped projects become more profitable for both the clients and companies. His passion to Innovate new processes and technology in BIM continues to help transform challenges to opportunity and problem to successful solutions.
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      Transcript

      ENRIQUE GALICIA: Hello, everybody, to Unlocking APS Insights. It's going to be a talk about data visualization for strategic decision making with Insights. This time, I'm talking with my friend and colleague Ravi Wood, which I would like to introduce. So, Ravi. Ravi Ray Good is an expert BIM manager in architecture with projects in US, Canada, Europe, Middle East, Singapore, and India.

      Top rated speaker at Autodesk University 2019, 2021, and 2023. Member of Autodesk University Advisory Council. Top rated speaker at HKIBIM 2016 in Hong Kong BIM. Award winning speaker at RICS IFMA 2018 Sweden and successfully lead over 150 projects in BIM globally, up to one trillion USD. So, Ravi.

      RAVI RAY WOOD: Awesome. Awesome. Yeah. Yeah, thank you. Thank you, Enrique. That's very kind of you. I really appreciate that. And also, welcome, everyone to the Autodesk University 2024, The Design and Make Conference. And with that, let me also introduce my really good friend, Enrique Galicia. Enrique is a BIM specialist. He's also the Dynamo ninja. He is APS guru. So if you have any questions on APS, you can ask him. He has tons of experience, not just 17 years' experience with the BIM workflows and software development.

      He's also done large scale projects across the globe, USA, Canada, Europe, Middle East, you name it. He has done the work. He's also been recognized for optimizing resources and streamlining projects, project delivery throughout the industry. His expertise is something that we all look forward to in the industry. If anybody has a question about AI integration, Dynamo, APS, Enrique is the person to go.

      His online courses, he's also a teacher. He has taught more than 30,000 students globally, and that reflects his in approach. He has people who has learned from him across the globe, so I am really grateful to be here with him today, and I think it's the same for all of us. Let's come on and learn together. So with that, we'll go to the next slide.

      ENRIQUE GALICIA: Yeah. Appreciate it, Ravi. So yeah, let's jump into the objectives and, therefore, how we're going to separate the lectures so that everything gets very clear. So the first one of them is to specialize in Autodesk Platform Services Data Visualization. So a lot of things happen when you don't know how to place things so that you can see them or how do you present them. So we're going to see some techniques for clarity and innovation.

      RAVI RAY WOOD: Awesome. Our second objective today is to identify and solve operational bottlenecks throughout the strategic data analysis.

      ENRIQUE GALICIA: Yeah. Third objective will be to utilize real time data to improve decision making and project outcomes, knowing that this is something that normally goes upon when you have a digital twin or you're using it on a construction, but it also can happen upon changes in design or also in feasibility.

      RAVI RAY WOOD: Awesome. And our fourth objective is to really look into and explore some real world case studies to transform planning strategies. And I think that's crucial for anybody who is here today. I think those sessions will-- that's the core of the session.

      ENRIQUE GALICIA: So let us start by defining the industry challenge. I mean, there are three main components that we are trying to aim on this presentation. That is like the overwhelming data complexity, like the industry giants. Like Tesla struggled with the vast complexity of data which can hinder sustainability and exploration.

      The data is multiplying, it's being much more bigger, and therefore, we need to have better systems so that everything can get very digested. The second one will be the ramp of AI implementation. It's been a buzzword that is working with a lot of systems in the middle, but how do we approach that ones if we do not use systems that can be blending?

      Or how about we call LLMs, we call our machine learning or our deep learning type of technologies into actionable items to nurture our work in progress. And the last one, I thought we also did it on these same sessions, that is the technology industry, that it's like having an effective leadership towards AI, automation, and technology to have a strategic oversight, fostering sustainable innovation and efficiency.

      RAVI RAY WOOD: Awesome. Now that we saw the industry channel, in the next slide, we'll go more about APS and how it can bridge that gap.

      ENRIQUE GALICIA: Yeah, so that APS brings the gap because it's not a specific system or product. It's just like a lot of frameworks that can allow us to help from different types of product outcomes to connect to other types of APS. So that APS bridge the gap by turning complex, fragmented data into automation action items. Also APS empowers teams. I will say that the trick within that one will be to know which data you want to flow and how does that one needs to be crafted on an automated process.

      And the third one is APS also integrated workflows. Make things seamlessly so that it can change chaos into clarity for a smooth, modern interface. So then we have this connection that's setting-- we talked on our previous lecture that was connecting the dots, the people and the technology. And we need to wrap up this discussion because we have seen that the user experience will make the complete change on that one. It's not just about using a product or using a software, but how does that one relate to each one of the ones that are working on a workflow will make the differences.

      And in particular, in this case, APS is very good on that matter, because you are actually having information there being digested on different types of automation, data exchange, review of files, and therefore you can bring it on any type of interface you want to have it. If you want it to have it mobile, web development, or also in the same product interface. So the importance is to combine people with the right technology. And within that one, APS will set up this setting.

      RAVI RAY WOOD: So--

      ENRIQUE GALICIA: Yeah. You're going to take it over? Yeah, go for it.

      RAVI RAY WOOD: Yeah, sure. No, I just wanted to say that's such a great start to the presentation. And now, we'll go into the more in-depth session overview. Yeah, take it forward. Enrique.

      ENRIQUE GALICIA: Yeah. Particularly, I will say I will recommend to review also the design strategic technology industry talk that is already within the same class-- within this set of classes, because on that way, there's also a lot of visibility on how technology get approaches. And in this case, we're very studying on the APS, expanding, whatever is happening with that one. So let's just jump for the APS data visualization techniques. I think this is very crucial on the process because normally it's not seen that clearly.

      So for the overview of tools, let's just jump to it. We have different types of solutions that happens to work on APS that are related like this. So that we have data structuring and exchange. We have two models. That is the AEC Data Model. The AEC Data Model is a framework we can use on APS, having a license and opening that organizes the project data so that we are reading and accessing management files from the ACC cloud.

      The other one will be the data exchange so that we can have changes in between different systems. So files that are from a specific type of naming or product can be changed or can also be triggering other types of elements. The next one we have is design automation on the automation and efficiency workarounds. So we have design automation which enables to have a plugin that is run on a bundle. And therefore, if we have it, we can just trigger an action from some content we have on a web page, on a mobile, so that it triggers and do changes even on a single file to be downloaded or working on the Autodesk Construction Cloud.

      The other one for automations will also be Autodesk Construction Cloud because we can also add any type of efficiencies, type of markups, things that are needed for that to work around. And we're doing a very close workflow for that data. The third set of selected solutions of APS is the user of the viewer. So normally a solution of APS normally looks like having a viewer with a lot of tools, but the viewer is just like an exit point. Like, it's a way of seeing things very quickly because you don't need to open the files directly on the product.

      You can review files that are from Revit, from AutoCAD, from Inventor. And therefore with that, what's happening with that file if it gets uploaded and then you can review it. The same thing happens with data visualizations, that it means it can read data from there and having different types of graphs. So that information is related to the files inside of it. And we have at last the early stage design and planning, which is things happening on Forma, because Forma works as a product but also has interface with the APS workarounds. So things that are happening there running from Dynamo scripts and things are also available to happen on Forma.

      So we have this image, and I would like to ask-- it goes from how we set the connecting services that we can find out which solution works best for a particular workflow or for a particular industry. So my recommend for that matter would be to streamline workflows so that we can know which solutions can be happening around it. And also I will say, if you can ask for consultancy or you can ask for some help, that will also aid things to happen, because there's a lot of information. It might be overwhelming. And the best way to work it around will also be to test to know that it's working already. And as we said it on the previous panel, to have a low hanging fruit effort so that with low, we can find out the return of investment.

      RAVI RAY WOOD: Awesome. I really like the real time data part.

      ENRIQUE GALICIA: Yeah, yeah. Yeah. I think it breaks everything. Having real time data is just like having power to have decisions on the right spot and working very nice.

      RAVI RAY WOOD: Awesome.

      ENRIQUE GALICIA: So let's go for a workflow. Very simple. I mean, very simple steps that you need to have for an APS. You need to create an account. You can use it from a trial service or you can just have it like signing up for an account and then have that service for a year going around. That first step leads you to become a developer, and from that developer, you can create a product. So products normally will request which is the APS service you want to use. It's very simple process, and you can check on the handout some reviews or workarounds how to set that working.

      Then once we have created a project, we will have to credentials because everything needs to be on a security policies. I mean, you cannot just ask-- you cannot just start working on a project and just review the data from everyone. You need to have a two security token, authentification token. So for that to happen, you need to have a client ID and also specifics from the app you are developing. Once you have already set it, you will need to ask on the programming services to get an authentification token.

      So very similar to a lot of things in the devices. I think that that's just a basic process. Normally a lot of people get stuck in this spot because it might get too techie, but once you have it from there, there are a lot of references that can be taken around it. So with your client ID and a client secret in hand, it's easy to set up an authentication.

      So within that token, everything is secure and your data is not being vulnerable to other things happening. Then the first slide I'm putting here is just the step number five is to connect to APS for data management. And there's also a lot of samples working on the API. So now let's go to our first type of objective that is about visualizations. Awesome.

      RAVI RAY WOOD: Yeah. Let's go more about the visualization. What I really like is how, in 10 minutes, you explain everything, how to sign into the network. You made it so simple and easy. I think everyone should do it.

      ENRIQUE GALICIA: Yeah, I think-- yeah, it's a process that takes longer than that because you need to have all the requirements. But I don't want it to have everything going too technical, just having a general overview. And I think that will sparkle the right, right? Sparkle the candle so that it goes like, oh, this idea might be taken forward and this might also work around on a different page.

      RAVI RAY WOOD: Awesome. Yeah.

      ENRIQUE GALICIA: Yeah. So I will say that from visualizations, it depends on how you want to tackle the issue. So three things that are important for visualizations is the essence and focus. You need to be easy to understand. It needs to be segmented. You don't want to see the other things. There's this thing happening within a Revit model that I always have thought that is like normally when you're trying to view it and you have all the data happening, the views only goes like looking through the needle, right? Looking through a small needle because you need to have filters, you need to have separated information.

      And normally if you define that on a workflow or make it standardized, that simple change in information to be seen makes a radical change. Like, because it's easier and it also can go to different stakeholders so that they can work better. So defining visualizations goes-- and essence and focus is to understand. Then the second one, it's very crucial on the terms that it goes for the user experience. Working on a user experience means it needs to be interactive, it needs to be engaging, it needs to be adjusted.

      If the data is already available, it needs to be very crafty so, in that case, they can use it, they can change it, they can even ask for different type of features without asking for IT support. And the third one would be that any visualization should be adaptable to growth. It needs to be used from one user, but also at the complete company, or also perhaps becoming a product that is workable for other companies to have a better result. Great minds think alike, and that would also nurture the things we're doing.

      So about that one, I mean, I will say, I'm just going to go for some types of graph. So some types of graphs, some types of visualizations, and, therefore, if there are some things that we need to address, probably that would be great. So the first one will be just graph visualizations. It's very simple, happening two dimensions. I will say that my only issue with graph visualizations is normally it doesn't make justice of what's happening. Like it goes too plain because things doesn't have normally just one set of values.

      Yeah, you can have expenses happening. But yeah, if the expenses are just growing, it doesn't tell you anything. But if you have a mixture between income growth within sustainability policies or you have it within like technology investments, perhaps that crackles the difference. They will just tell you where it goes. So it's useful for showing trends, for showing simple data, and also for have visual relationships. So the things happening on a net-- and it's been a lot of changes, but it normally comes to very simple graphs when we try to see things.

      And I'll say that from that one, it depends on which is the technology map we want to follow as a strategist. The next one, I put it-- particularly, I like it a lot. I mean, I think this image goes a little with too much information. But I place it in this case because procedural visualizations is something that is very useful. It means that the things are generated as the data is coming available. It's something that is not just written in graphs, but also, where is that detouring?

      And I'll say that that approach goes in hand within the use of AI. Like, if the data is being introduced on a vector database, then therefore it can be query, and therefore it can have trends of, where do you think it will go having multiple data at the same time. So within these type of visualizations, I know it's dynamic, it's complex, but still, it gets you within the feeling that the data is not just there. Like, it's having their own behaviors. So what could be your thoughts about this one, Ravi? What do you think?

      RAVI RAY WOOD: I think the visuals are great. As you said, this one-- and the most important thing is the information. The way you said it's a collage of dashboards, that make sense, not just one particular information. And as you have pointed out here in the slide, that it's very important to identify the bottlenecks quickly and make good decisions.

      ENRIQUE GALICIA: Yeah. Sure from that one. I mean, it's like the best use for procedural will be to map workflows, know where the trends are going, and to identify bottlenecks. So that you know, wait, we haven't seen that one happening. And it's just, keep on producing with their own data so that we know where it's heading up. So I will say that that type of the things that are about to come there will be very useful in the future because right now with computational power and being a lot of generative AI working in hand, probably that will also become into settings.

      So next type of visualization is 3D visualization, which comes in hand that we have models, we have a lot of elements, we have elements that are three dimensional. And also, the data wouldn't be fair for it to be just very plain. We have three dimensional things happening. We have time being an addition, cost being within other types of values.

      So 3D visualizations is very useful on the games that we are using the viewer, the viewer can be interactive, the viewer can be connected with the data as it's flowing, and we have those two things that are exploring it visually makes a difference on the visibility. It's not just like it's growing, but it's actually where it's growing, how it's growing. And even though we were talking about things happening on flow or having on a type of multimedia working around that when you're having those visualizations, using it from the power of the APS and all the files that you have there, you can have something that changes the way of looking of things.

      RAVI RAY WOOD: Absolutely. I think the perspective can change because you get so much data in such quick time.

      ENRIQUE GALICIA: Yeah. Exactly. It needs to be relief on the right moment, and because you already have that data, I mean, it will be just very useful. Then we also have case study, case setup visualizations. That wouldn't be like something you program as an application, but rather from something related to the workflows. And we were talking about, yeah, technology strategies happening in a company always need to be aligned to the business case. So it would be very fair that within this specific type of visualizations, it's like we are creating something that simulates the scenarios.

      So we have prior projects that are working and, therefore, how do they seem like? What will be the key factors that are case setup visualization should have? And therefore, these type of visualizations that doesn't go into being procedural, just graphical or three dimensional, but also something that goes on a case study type of logic. Right? Yeah, we're creating another building. How is this one compared to the other ones, and how we can improve it.

      Then we also have any other type of response, depending if we want to have insights, if we want to have it something driven from the client's perspective. Like, if they are getting involved or something that we want to develop on that matter. I will say that at this time, information being flown and a lot of language models helping with code, programming specific solutions shouldn't be as complicated as it was probably will be a key factor that can change other things. So from that, yeah, I will say choosing the right tool will be the great one. Yeah?

      RAVI RAY WOOD: No, yeah. I'm with you. Especially as you said. Yeah, let's move on to the-- I'm really excited about this section. How do we choose the right thing for a particular need?

      ENRIQUE GALICIA: Yeah, exactly. Exactly. I would think that that's the question. What's the one that will show us better workflows, or what will be critical and how that one works. So let's go and jump into the next section. Section number two. It goes against strategic data analysis to prevent bottlenecks. So from my perspective or from being placed upon the presentations, we got it on different environments.

      We have bottlenecks happening on feasibility. That will depend on compliance. It will depend on things that are sustainable. Bottlenecks happening on design. That is like a lot of things being created at the same time will have conflict if they don't have the proper information to flow around and to see how the project will move forward.

      Then we have bottlenecks happening on construction, which will be the ones that are leading upon missing information, things that weren't solved, or things that are getting solved that the project is evolving. And then at the end will be bottlenecks happening on digital twins. Like if information is being placed and it's being used for further uses on a digital twins perspective, that will be around it. So let's jump into those, and then if there are any concerns, let's work around it.

      So first one is Forma. So Forma is fighting for feasibility. I will say, we used it on the previous talk, talking about Forma integrating things on a contextual level, happening information from projects being assigned to that one, working on sustainability tools that may lead for that one. So yeah. So main concern about bottlenecks happening in Forma is to do visualize design options to see how those changes impact on the general overview for that to make it feasible, and also to assess feasibility with regulatory compliance, bylaws, and environmental requirements.

      So yeah. So in this case, it's a proactive approach that ensures that potential issues are spotted and addressed before they become roadblocks. Like, we don't want to get blocked, and as soon as earlier we get feasibility working around, we can use Forma. And Forma, in this case, we're using it through the APS.

      RAVI RAY WOOD: Great visuals.

      ENRIQUE GALICIA: Yeah. I'm glad you like it. They're trying to get the essence, like the essence from wherever we're looking upon. So in that case, they are very reflecting. So this other sample goes like, yeah, we have the Forma on the low level context, but we can also use it for Forma for urban planning, having diverse sets, having TD regulations, and have traffic patterns. Like within the platform in Forma, it goes very simple with the three dimensions, and it can also allow us for that to be pushing around. So we can visualize those elements. We can even visualize it with graphs, with procedural, or having other additional and three dimensional models.

      Then we can also have that urban planning poses unique challenges in integrating data sets such as zoning, infrastructure, and environmental factors. So yeah. Just like us getting reinforced on this section, APS format can use it to be optimized on urban development, ensuring designs meet regulatory requirements while promoting sustainable resource use.

      And I think we flow a lot of things on sustainable terms so that things are important to be known and as well, all efforts can be nurtured with an AI. Like, having language models to be included into the process so that it's not just information you are creating but also how the assistants or how the other language models are helping you to get deeper known on these topics.

      RAVI RAY WOOD: Awesome. I think this is informative for all of us.

      ENRIQUE GALICIA: I think it's also like a lot of information, but try to concentrate it so that it goes very simple on that case. So yeah, just putting here samples that are happening there. It's like optimizing urban development and also driving sustainable planning. Then there's also comprehensive data integration. The more we can see, the better we can react, or we can have a better decision taking and informed decision making as well. The factors we are looking upon, they can also help. So from this spectrum, then, going to the next step is we already see feasibility.

      Second step will be on design challenges. So within design challenges where you use of generative AI and database integration because it's no longer just being creative, being adding elements from the graphs, from the schematic design, but it also is how that information is being stored, how it is being produced. We're getting to the conclusion that the connection of LLMs and the connection of different tools shouldn't be on a fight against a workflow. They are also tools that are adding settings around it.

      So within this slide, it's about the dynamic data representation, how does that data that you are creating it by hand but also the one that you are prompting for generative AI to work around gets connected on a server, server being called, and then APS showing that on a project. How to query a vector database. So we know that a vector database refers when you have a database that is being collected so that when you're trying to read it with machine learning processes, it's pointing out to the solution faster, and that way it speeds up the resolution.

      So the use of vector databases is also a process for doing analysis on the APS. Maintaining standards, streamlining the data flow, and optimizing the project information. So as the things get together on a project design perspective, the better we can extract them and have visualization for the team to ensure that they are doing the right decisions. That's the way things will be getting improved.

      Then we have things talking about the visualization the impact design choices. So one common thing happening on design development is that the changes and the possibilities are still on this type of reviewing. So with APS, Forma, and also using APS Data Exchange, we can visualize the impact of design choices, connecting it to other factors such as cost, such as time, avoiding to have silos, and having the scenarios to be connected so that the influence can be driven upon and this data driven approach can enable the selection of designs that optimizes sustainability and enhance livability.

      RAVI RAY WOOD: Yeah, I totally agree with you on the silos. I think that's so crucial and critical to have no silos. This is great process workflow.

      ENRIQUE GALICIA: Yeah. I can imagine that if the silos are very separated, it's very complicated. It's complicated also to develop something, but if you have the APS services, you have a spot where you can save your information, you have a standardized workflow, then, therefore, taking the decisions will be easier because in that case, you can have your graphs, you can have your models, you can have your data, you can have your costs going in the middle. And therefore, within the impact of changes, just having connected so that everybody is on the same decision board.

      RAVI RAY WOOD: Wow. So it's like a one stop for one source of truth for information and changes are much faster.

      ENRIQUE GALICIA: Yeah. I will say that putting it in that perspective is we have a CDE accommodate environment where we have everything, but then the APS, it's a flexible type of frameworks that helps you to connect the dots in between everything, and therefore also connect it to AI so that you can see it somewhere else or you can see it on a proprietary technology or using technology from others as well.

      RAVI RAY WOOD: Awesome.

      ENRIQUE GALICIA: So yeah, just some key points on this one is like design development to be for optimizing design processes, enhance team collaborations, reduce time to market, support data driven decisions, and improve design quality. So yeah, a lot of things to process upon happening on designs. So here I'm placing just a sample that this is what goes on the project development phase. So this is an assistant that it's-- for mobile [INAUDIBLE].

      What it does actually is it is connecting to a LLM model working on Revit or working on a web service. So what it does basically is that you can have your questions and you can use different type of assistance, but this one is aided upon the use of Revit, the use of things happening on the cloud services and also within other software solutions. So in this case, it's showing me that I find it an error. I can just ask the assistant that it's working natively, and therefore, it can also improve the workarounds.

      RAVI RAY WOOD: Awesome. I think this Andiamo feature is awesome and it's going to be so helpful for any Revit users, even if they are new to Revit or intermediate users, or even expert users. I think it's going to be very, very crucial.

      ENRIQUE GALICIA: Yeah. I think from that one, it's very understood that the clients are always changing the way the tools are working and as well within the products. Like, we are on an era that communications and new strategies needs to be blended in because that way we can get stronger. Like, it's too much information. It's not just one single source of truth, so that the more we connect, the more we interact, it's going to be better.

      RAVI RAY WOOD: I agree with you. There is so much information these days, and if we can simplify it, make it better, great.

      ENRIQUE GALICIA: Exactly. So just pointing out some strategic resolutions. We're putting here, OK, so key points happening here is like identify bottlenecks early. The better we know where we're getting stuck, it's something we need to work either on a workflow, either on standards, and therefore we know that we have those working in place. Then we can just ask for a solution or create a solution that is getting the advantages. We have an APS set of frameworks, but also we can also use some other language models working in the middle.

      Then ensure project continuity so that the things are happening from the project development to the-- the product development to the construction development. Leverage visualization techniques. The better we are showing things, the better we can change them, the better we can take decisions. Enhance team coordination and support project success. So I'm going to stop for a moment. This is, I mean, an image working around it. I mean, I know that that will be if the complete office is working on an IMAX type of theater, having a lot of things happening in the middle.

      RAVI RAY WOOD: I really like this idea. This is such a good visual of what we're building. It kind of also gives the scale of what we're building, too.

      ENRIQUE GALICIA: Yeah.

      RAVI RAY WOOD: It's a great, great-- yeah. Awesome.

      ENRIQUE GALICIA: Yeah. I would like to point out from this one is like, yeah, remembering that user experience, the use of technology, the use of connecting the dots will be something that can enhance and also can unlock the APS users. Like if you know what you're missing or where is your bottlenecks, therefore there might be a product that can help you to solve that and make everything faster on a better pace. So the transformation from problem identification to collaborative solution is key to driving a project success. And yeah. I mean.

      RAVI RAY WOOD: Yeah. This slide is pretty self explanatory. First, you need to identify, find a solution. But even once you have a solution, it's very important to collaborate, because you have to work with people, your work as a team. And then even when you start collaborating, you have to continuously have strategic interventions, pivot, pivot, pivot, pivot. We have to be flexible. And the most important thing is unless you empower your team, the success is not going to come. It's not an individual sport. And that's how you can have sustainable success and growth, by working as a team collectively, being ready to pivot, and finding new solutions.

      ENRIQUE GALICIA: Yeah. Exactly. Exactly. I couldn't say it better. Yeah. So the third section happening on the objectives is like, OK, we have seen-- I'm doing a small recap. First objective, knowing different types of graphical visualizations. Second round is finding bottlenecks that might become part of the things we can ensure it can connect to the graph so it can connect to decision taking or something happening on AI.

      And the third one we're using is utilizing real time data. And the reason behind this one is that the objective of having real time data, it can allow you to do changes on the right spot. Even though real time data can happen on the design phase, it can happen on the construction phase, having the real time data is just that you're not just within the drive that the project is pushing but also having a way of seeing it around it.

      So the first step will be to ensure that all data sources, whether they are design, construction, or on-site activities, are connected and accessible. So by linking the resources, we create a foundation where information can flow seamlessly across the project lifecycle, supporting real time tracking and informed decision making.

      So first case scenario on construction flow. So we are going to blend some things from the objective four happening on case studies. And in this case it's like this can be just a single scenario. The scenario goes, yeah, we have the data feeds, we have relevant data sources as sensors, IoT devices, or external streams.

      So how the information is getting into our servers, our data collections. Then step number two will be integrated with APS so that those connections are called by an API or they are already review, read it. And the third one will be like, OK, validate that accuracy. So if that is being validated that you are using the correct data on the right spots, then you can visualize it. And within that visualization, then decision taking takes place.

      RAVI RAY WOOD: Awesome.

      ENRIQUE GALICIA: Then another sample is integrating building systems with APS Viewer. So that means this one is going on, a sample happening already on a site using a digital twin. So APS Viewer allows you to integrate all the building systems into a single interface. This seamless integration means you can monitor HVAC, lighting, security more than one place. The thing you will need there is the IoT devices will need to be tracking which is the performance that you're having on a specific happening around it, and decentralized view enables better management, quick response to any issues, and overall, the efficient operation of the building systems.

      RAVI RAY WOOD: Awesome.

      ENRIQUE GALICIA: Yeah. Then we have another sample that is visualizing real time data that is like, OK, as you are creating it, if it has some sort of RFIDs or something that it's reading upon, you can see things as they are happening, monitoring real time data to spot trends and anomaly, to have dynamic visualizations, interactive graphs. I mean, they can be within the data that you're having or something that goes more fluently. And stay informed so that you can have real time updates.

      Then maintaining data quality is essential for effective real time monitoring. Setting up real time alerts with APS can notify you and have any irregularities. Remember that we saw on the first ones that we also have design automation? So we can also use webhooks so that the things that are being changed, if something goes within the servers, then it can pop up.

      And it depends if it's popping on a cell phone, it's popping on a web service, or something else. Regular validation checks and updates for your data streams ensure that your real time data remains reliable, supporting accurate and effective decision making through the project. Then we have another example-- yeah, you wanted to? Yeah?

      RAVI RAY WOOD: I just wanted to say the slide looks great, and yeah, let's get into some practical examples. Yeah.

      ENRIQUE GALICIA: Yeah. So this is a sample happening within real time data in action. So let's consider a project where real time data integration was crucial. In this case, a construction project faced potential delays to unforeseen environmental conditions. If the data from the site is being already distributed to the servers, I mean, by integrating real time data weather that into APS, the project has the ability to adjust their schedule dynamically, avoiding costly delays.

      The real time data allow the team to make immediate decisions based on current conditions. So within these ones, it can allow to know, OK, if we're seeing that our project is going to get snow and we are not ready for the conditions to change in the next days because we have our programming schedule, then, therefore, if that data is connected and then that connected server goes within the elements that are going to be played, then we are seeing upfront things that can become risky on our process creation.

      Then real time data is more than just numbers on a screen. It's a powerful tool to make informed decisions that keep your project on track and ahead of the curve. By leveraging real time data in APS, you can enhance decision making process, ensuring that your actions are based on the most current and relevant information. This approach allows the team to adapt quickly by changing project conditions and collaborate more efficiently, ultimately driving project success.

      Yeah. Then samples happening on building operations and maintenance. I think that one goes as well within real time planning because as the project is getting ready and it's already finished, probably not too many people will be there. But also, the information happening on real time will be more crucial because the better it's connected, the better we can know what's happening. So it's like it can help optimize operations for predictive maintenance and also for reduced operational cost.

      And there was a sample working around that one. We have it on the company from an airport that, within the use of real time data from lighting, it starts having some reduction costs without having that being part of a costly process. So it was like because of the real time data that the project was able to be improved when it was already finished, on something that it's already been built.

      RAVI RAY WOOD: Awesome. Yeah. That's such a great example to use it on the airport.

      ENRIQUE GALICIA: Yeah. Definitely. So one of the key advantages of real time data is the ability to monitor trends as they develop. We have already discussed that one within the AI being predictive and also having some procedural type of images. Whether it is tracking an energy consumption, project progress, or any other metrics, real time data allows you to see patterns as they emerge, like they have it. So those unexpected deviations from the north that can indicate a problem will be type of what we're trying to avoid, to make the steps and to make the project stay on track.

      Then with real time data at your fingertips-- because with the advantages of APS being unlocked is that you can have it on a mobile, you can have it web, you can have it desktop. So having it, it will make it that it's easy to use it for guide your actions, ensuring that every decision that you make is backed by the latest insights, reducing the risk of errors and increasing the likelihood of a success.

      RAVI RAY WOOD: All right. Let's get into some case study about adaptive planning with real time data.

      ENRIQUE GALICIA: Yeah. So I mean, this case is just like, put it on that one. It's like, look at the scenario where real time data play a critical role in decision making. A construction project encountered unexpected supply chain disruptions. And we have seen that one, that when something happens or some product is being driven very far away, you can just change it.

      But by monitoring real time data from suppliers, the project team was able to quickly identify the issue and adapt their plan, changing which elements are not going to be in time and how they need to be relocated. So within this example shows that real time data can turn potential setbacks into opportunities for adaptive informed decision making.

      RAVI RAY WOOD: Great.

      ENRIQUE GALICIA: Yep.

      RAVI RAY WOOD: Let's look into some how to enhance operational efficiency, because the energy bills-- imagine not just when our house gets such big energy bills. For bigger buildings and airports and hospitals, if we can save on that operational cost, I think that's such a big, big positive money coming in for the company. So yeah, go ahead, please.

      ENRIQUE GALICIA: Yeah. I mean, just putting on this one, that enhancing operational efficiency, it's also part of using real time data. Using APS Viewer, the building management team is able to enhance operational efficiency, optimize energy use, reduce downtime, and cut costs.

      RAVI RAY WOOD: Nice. I like cutting cost.

      ENRIQUE GALICIA: Yeah, of course. Yeah. It goes into cutting cost, but also I will say like reallocate resources so that they can keep on having more technology assets happening. Technology assets is a game changer. It's also part of a way of unlocking APS possibilities. The more technology you have and as well, if it's very well founded upon the user experience, therefore it will always retrieve back.

      RAVI RAY WOOD: Awesome. Yeah. Cut costs, save money, save time.

      ENRIQUE GALICIA: Yeah. Yeah, indeed. So real time data in construction management. It would be like tracking project progress. So knowing where things are happening around resource allocation and on-site conditions. I would say that at this point there are a lot of APS Viewers working within schedule and also with time for the planning, because that seems like a very nice use of technology. Rather than just having everything manually being added to the Revit model as a priority, as a property or a parameter, or as a database working on Navisworks, having it on the APS means that you already have it on a server that is connected to other services and other previously taken projects.

      So yeah. I will say also for on-site conditions, as we saw the sample of the snow happening in the middle. So also real time collaboration and communication happening on the construction side. Like working with streamlined communications, shared dashboards, so that the things that are happening in a project can also be applied to a different type of project and data driven decisions.

      So another content happening is that real time data also plays a crucial role in maintaining safety and compliance on construction sites. By the use of APS tools, project managers can monitor conditions, receive real time data safety alerts, and track compliance with regulatory standards. Using things from cameras also, and using computer vision as one of types of artificial intelligence, it will also be connected to a type of working environment when things are getting built.

      RAVI RAY WOOD: Awesome. Yeah. Safety comes first, so yep.

      ENRIQUE GALICIA: Yeah. And also real time integrated with project delivery. Knowing how the milestones are working around, how will they be placed upon when they are being created, optimize resource allocation, and ensure timely delivery. As we were seeing on the sample of procurement being on-site, also by the use of APS, that will also be very good to have. Yeah.

      RAVI RAY WOOD: These days, with the long lead times, everyone's moving towards the IPD or lean integrated project delivery. So when we are doing that, I think this becomes so crucial because you have that one source of truth, which is real time data to make good decisions. I think this is great.

      ENRIQUE GALICIA: Good. So just another image. We can have some visibility from that happening. Yeah.

      RAVI RAY WOOD: Awesome. Yeah, let's--

      ENRIQUE GALICIA: Yeah, and we're almost heading to the end. So yeah, I will say that just like real time data going for a predictive analysis is to do a forecast of outcomes, use real time data to predict success and challenges, identify risk areas, and optimize resources. So within this set and within all this content and these case study samples, I mean, we're heading up to the conclusions.

      I will say, as we conclude our journey through the integration of Autodesk Platform Services into the AEC industry, it's clear that these tools provide powerful capabilities for enhanced project management, improving decision making, and fostering continuous innovation by seamlessly connecting real time data, leveraging advanced visualization techniques, and applying strategic insights. So IPS empowers teams to achieve greater efficiency and success in their projects. So a lot to cover in just one single presentation. But I think like within this one, I hope you have several conclusions.

      RAVI RAY WOOD: Yeah. Mike, I think the conclusion here is this is such a great start for APS, and I think the journey for all of us ahead is just getting started. We are all getting started now.

      ENRIQUE GALICIA: Sure. Sure, it is. So just some recap happening. So APS conclusions is integration, having things on the same resource so that they can be changed. Real time monitoring. If the things are getting connected with real time data, they can also be changing visualization happening. Visualizations. That is not just about having single graphs and having objects on the screen from the 3D model but also how those all get built upon knowing what's happening and also to foster collaboration.

      The data is not just from the ones that are modeling but also everyone that is having access to it can make decision taking, improve the data, and having it around it. And from the unlocking perspective, we have it as data driven decision making is something critical when you have standards and workflows so that, therefore, information is there. Just pull it out, use it, and that will also lead into something being supported by decision driven.

      Also efficiency in project management, which would be like automating routines, streamlining workflows. APS can also help you to do that one. The things that are already tedious or routine can also be working within those processes, and the last one will be continuous improvement. The better we know each other, the better we can improve.

      RAVI RAY WOOD: Yep. I agree with you on continuous improvement. All right, let's have a call for action.

      ENRIQUE GALICIA: Yeah. So I'm just putting those two settings within BIM slightly different because of the green factor happening with sustainability. And I will say that the call for action would be like, yeah, I mean, it's a tool that it wouldn't be as complicated as it is to create a standardized workflow. I would think that if the thrive is already there and the users are already there, then the call to action to try something might be very nice idea. Always recommended to be on a low hanging fruit effort.

      And yeah, API lies on a strategical use. I mean, I will say that nobody will use it unless it's very related to something strategic. The better we can know the information is how we can change our business case to work better. And yeah, you can also always reach for support. I'm putting this slide around, it's like [INAUDIBLE] accesses.

      RAVI RAY WOOD: Yeah. If you have any questions, Enrique is the APS guru. So if you have any questions-- and Dynamo ninja. Reach out to him. That's the best way to learned something new. If you reach a roadblock or bottleneck, reach out to the experts, ask them a question. So, yep, that's our connection, and please--

      ENRIQUE GALICIA: Yeah. And as well, I mean, any type of feedback or review on how your technological processes are going as well as how you can implement having a standard things working in the middle within project design, project development, just as well as Ravi, he's very-- I mean, he's great on all those matters as well having a lot of experience, and also within communicating, like improving communications workflow. So I will say that that's a great to take. Yeah.

      RAVI RAY WOOD: Awesome.

      ENRIQUE GALICIA: So also remember to vote on the survey. Hopefully within that one, this was a great lecture for you so that it will also improve within the technical elements and having a great visibility on how to get better results going around it.

      RAVI RAY WOOD: Yeah.

      ENRIQUE GALICIA: And yeah, I would like to say a big thank you.

      RAVI RAY WOOD: Same here. Everyone, thank you so much for coming in. We appreciate your time. Enrique, it's such a great class. I mean, this is awesome. The in-depth knowledge you have and what you're trying to do for the industry, it's remarkable. I think it's a very pioneering effort. So really, thank you to you for that.

      ENRIQUE GALICIA: Thank you as well, Ravi. I mean, your insights have been great. And as well within that one, it's always trying to collaborate because great minds think alike, right?

      RAVI RAY WOOD: Awesome. Yeah.

      ENRIQUE GALICIA: Yeah. So hope you continue enjoying the AU 2024, The Design and Make Conference.

      RAVI RAY WOOD: Awesome. Thank you.

      ENRIQUE GALICIA: Thank you.

      ______
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      Utilizamos los servicios de ClickTale para entender mejor en qué áreas de nuestros sitios puede experimentar problemas. Grabamos las sesiones para ver cómo interactúa con nuestros sitios, incluido cualquier elemento de las páginas. Su información personal identificable se enmascara y no se recopila. Política de privacidad de ClickTale
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      Utilizamos los servicios de OneSignal para mostrar publicidad digital en sitios respaldados por OneSignal. Los anuncios se basan tanto en datos de OneSignal como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que OneSignal haya recopilado de usted. Utilizamos los datos que suministramos a OneSignal para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de OneSignal
      Optimizely
      Utilizamos los servicios de Optimizely para probar nuevas características en nuestros sitios y ofrecerle una experiencia personalizada con esas características. Para ello, recopilamos datos de comportamiento mientras visita nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, y su ID de Autodesk, entre otros. Puede que acceda a una versión diferente de nuestros sitios debido a las pruebas de características que hacemos, o que vea contenido personalizado en función de su perfil de visitante. Política de privacidad de Optimizely
      Amplitude
      Utilizamos los servicios de Amplitude para probar nuevas características en nuestros sitios y ofrecerle una experiencia personalizada con esas características. Para ello, recopilamos datos de comportamiento mientras visita nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, y su ID de Autodesk, entre otros. Puede que acceda a una versión diferente de nuestros sitios debido a las pruebas de características que hacemos, o que vea contenido personalizado en función de su perfil de visitante. Política de privacidad de Amplitude
      Snowplow
      Utilizamos los servicios de Snowplow para recopilar datos acerca de su actividad en nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, y su ID de Autodesk. Utilizamos estos datos para poder medir el rendimiento de nuestro sitio web y determinar el grado de facilidad de su experiencia en Internet a fin de mejorar nuestras características. También empleamos sistemas avanzados de análisis para optimizar su experiencia con los servicios de correo electrónico, atención al cliente y ventas. Política de privacidad de Snowplow
      UserVoice
      Utilizamos los servicios de UserVoice para recopilar datos acerca de su actividad en nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, y su ID de Autodesk. Utilizamos estos datos para poder medir el rendimiento de nuestro sitio web y determinar el grado de facilidad de su experiencia en Internet a fin de mejorar nuestras características. También empleamos sistemas avanzados de análisis para optimizar su experiencia con los servicios de correo electrónico, atención al cliente y ventas. Política de privacidad de UserVoice
      Clearbit
      Clearbit permite el enriquecimiento de datos en tiempo real para proporcionar una experiencia personalizada y relevante a nuestros clientes. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Política de privacidad de Clearbit
      YouTube
      YouTube es una plataforma de uso compartido de videos que permite a los usuarios ver y compartir vídeos insertados en nuestros sitios web. YouTube proporciona métricas de audiencia sobre el rendimiento de los vídeos. Política de privacidad de YouTube

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      Personalización de la publicidad: Nos permite ofrecer publicidad dirigida

      Adobe Analytics
      Utilizamos los servicios de Adobe Analytics para recopilar datos acerca de su actividad en nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, y su ID de Autodesk. Utilizamos estos datos para poder medir el rendimiento de nuestro sitio web y determinar el grado de facilidad de su experiencia en Internet a fin de mejorar nuestras características. También empleamos sistemas avanzados de análisis para optimizar su experiencia con los servicios de correo electrónico, atención al cliente y ventas. Política de privacidad de Adobe Analytics
      Google Analytics (Web Analytics)
      Utilizamos los servicios de Google Analytics (Web Analytics) para recopilar datos acerca de su actividad en nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Utilizamos estos datos para poder medir el rendimiento de nuestro sitio web y determinar el grado de facilidad de su experiencia en Internet a fin de mejorar nuestras características. También empleamos sistemas avanzados de análisis para optimizar su experiencia con los servicios de correo electrónico, atención al cliente y ventas. Política de privacidad de Google Analytics (Web Analytics)
      AdWords
      Utilizamos los servicios de AdWords para mostrar publicidad digital en sitios respaldados por AdWords. Los anuncios se basan tanto en datos de AdWords como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que AdWords haya recopilado de usted. Utilizamos los datos que suministramos a AdWords para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de AdWords
      Marketo
      Utilizamos los servicios de Marketo para enviarle contenido más relevante y oportuno por correo electrónico. Para ello, recopilamos datos sobre su actividad en Internet y el modo en que interactúa con los correos electrónicos que enviamos. Los datos recopilados pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, la tasa de apertura de correos y los vínculos seleccionados, entre otros. Puede que combinemos estos datos con datos obtenidos a través de otras fuentes a fin de mejorar su experiencia de compra o con el servicio de atención al cliente, además de ofrecerle contenido más relevante en función de procesos avanzados de análisis. Política de privacidad de Marketo
      Doubleclick
      Utilizamos los servicios de Doubleclick para mostrar publicidad digital en sitios respaldados por Doubleclick. Los anuncios se basan tanto en datos de Doubleclick como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Doubleclick haya recopilado de usted. Utilizamos los datos que suministramos a Doubleclick para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Doubleclick
      HubSpot
      Utilizamos los servicios de HubSpot para enviarle contenido más relevante y oportuno por correo electrónico. Para ello, recopilamos datos sobre su actividad en Internet y el modo en que interactúa con los correos electrónicos que enviamos. Los datos recopilados pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, la tasa de apertura de correos y los vínculos seleccionados, entre otros. Política de privacidad de HubSpot
      Twitter
      Utilizamos los servicios de Twitter para mostrar publicidad digital en sitios respaldados por Twitter. Los anuncios se basan tanto en datos de Twitter como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Twitter haya recopilado de usted. Utilizamos los datos que suministramos a Twitter para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Twitter
      Facebook
      Utilizamos los servicios de Facebook para mostrar publicidad digital en sitios respaldados por Facebook. Los anuncios se basan tanto en datos de Facebook como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Facebook haya recopilado de usted. Utilizamos los datos que suministramos a Facebook para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Facebook
      LinkedIn
      Utilizamos los servicios de LinkedIn para mostrar publicidad digital en sitios respaldados por LinkedIn. Los anuncios se basan tanto en datos de LinkedIn como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que LinkedIn haya recopilado de usted. Utilizamos los datos que suministramos a LinkedIn para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de LinkedIn
      Yahoo! Japan
      Utilizamos los servicios de Yahoo! Japan para mostrar publicidad digital en sitios respaldados por Yahoo! Japan. Los anuncios se basan tanto en datos de Yahoo! Japan como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Yahoo! Japan haya recopilado de usted. Utilizamos los datos que suministramos a Yahoo! Japan para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Yahoo! Japan
      Naver
      Utilizamos los servicios de Naver para mostrar publicidad digital en sitios respaldados por Naver. Los anuncios se basan tanto en datos de Naver como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Naver haya recopilado de usted. Utilizamos los datos que suministramos a Naver para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Naver
      Quantcast
      Utilizamos los servicios de Quantcast para mostrar publicidad digital en sitios respaldados por Quantcast. Los anuncios se basan tanto en datos de Quantcast como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Quantcast haya recopilado de usted. Utilizamos los datos que suministramos a Quantcast para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Quantcast
      Call Tracking
      Utilizamos los servicios de Call Tracking para proporcionar números de teléfono personalizados como parte de nuestras campañas. De este modo, podrá acceder más rápido a nuestros agentes y ayudarnos a medir mejor nuestro rendimiento. Puede que recopilemos datos acerca de su actividad en nuestros sitios en función del número de teléfono facilitado. Política de privacidad de Call Tracking
      Wunderkind
      Utilizamos los servicios de Wunderkind para mostrar publicidad digital en sitios respaldados por Wunderkind. Los anuncios se basan tanto en datos de Wunderkind como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Wunderkind haya recopilado de usted. Utilizamos los datos que suministramos a Wunderkind para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Wunderkind
      ADC Media
      Utilizamos los servicios de ADC Media para mostrar publicidad digital en sitios respaldados por ADC Media. Los anuncios se basan tanto en datos de ADC Media como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que ADC Media haya recopilado de usted. Utilizamos los datos que suministramos a ADC Media para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de ADC Media
      AgrantSEM
      Utilizamos los servicios de AgrantSEM para mostrar publicidad digital en sitios respaldados por AgrantSEM. Los anuncios se basan tanto en datos de AgrantSEM como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que AgrantSEM haya recopilado de usted. Utilizamos los datos que suministramos a AgrantSEM para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de AgrantSEM
      Bidtellect
      Utilizamos los servicios de Bidtellect para mostrar publicidad digital en sitios respaldados por Bidtellect. Los anuncios se basan tanto en datos de Bidtellect como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Bidtellect haya recopilado de usted. Utilizamos los datos que suministramos a Bidtellect para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Bidtellect
      Bing
      Utilizamos los servicios de Bing para mostrar publicidad digital en sitios respaldados por Bing. Los anuncios se basan tanto en datos de Bing como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Bing haya recopilado de usted. Utilizamos los datos que suministramos a Bing para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Bing
      G2Crowd
      Utilizamos los servicios de G2Crowd para mostrar publicidad digital en sitios respaldados por G2Crowd. Los anuncios se basan tanto en datos de G2Crowd como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que G2Crowd haya recopilado de usted. Utilizamos los datos que suministramos a G2Crowd para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de G2Crowd
      NMPI Display
      Utilizamos los servicios de NMPI Display para mostrar publicidad digital en sitios respaldados por NMPI Display. Los anuncios se basan tanto en datos de NMPI Display como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que NMPI Display haya recopilado de usted. Utilizamos los datos que suministramos a NMPI Display para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de NMPI Display
      VK
      Utilizamos los servicios de VK para mostrar publicidad digital en sitios respaldados por VK. Los anuncios se basan tanto en datos de VK como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que VK haya recopilado de usted. Utilizamos los datos que suministramos a VK para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de VK
      Adobe Target
      Utilizamos los servicios de Adobe Target para probar nuevas características en nuestros sitios y ofrecerle una experiencia personalizada con esas características. Para ello, recopilamos datos de comportamiento mientras visita nuestros sitios. Estos datos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado, su dirección IP o ID de dispositivo, y su ID de Autodesk, entre otros. Puede que acceda a una versión diferente de nuestros sitios debido a las pruebas de características que hacemos, o que vea contenido personalizado en función de su perfil de visitante. Política de privacidad de Adobe Target
      Google Analytics (Advertising)
      Utilizamos los servicios de Google Analytics (Advertising) para mostrar publicidad digital en sitios respaldados por Google Analytics (Advertising). Los anuncios se basan tanto en datos de Google Analytics (Advertising) como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Google Analytics (Advertising) haya recopilado de usted. Utilizamos los datos que suministramos a Google Analytics (Advertising) para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Google Analytics (Advertising)
      Trendkite
      Utilizamos los servicios de Trendkite para mostrar publicidad digital en sitios respaldados por Trendkite. Los anuncios se basan tanto en datos de Trendkite como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Trendkite haya recopilado de usted. Utilizamos los datos que suministramos a Trendkite para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Trendkite
      Hotjar
      Utilizamos los servicios de Hotjar para mostrar publicidad digital en sitios respaldados por Hotjar. Los anuncios se basan tanto en datos de Hotjar como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Hotjar haya recopilado de usted. Utilizamos los datos que suministramos a Hotjar para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Hotjar
      6 Sense
      Utilizamos los servicios de 6 Sense para mostrar publicidad digital en sitios respaldados por 6 Sense. Los anuncios se basan tanto en datos de 6 Sense como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que 6 Sense haya recopilado de usted. Utilizamos los datos que suministramos a 6 Sense para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de 6 Sense
      Terminus
      Utilizamos los servicios de Terminus para mostrar publicidad digital en sitios respaldados por Terminus. Los anuncios se basan tanto en datos de Terminus como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que Terminus haya recopilado de usted. Utilizamos los datos que suministramos a Terminus para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de Terminus
      StackAdapt
      Utilizamos los servicios de StackAdapt para mostrar publicidad digital en sitios respaldados por StackAdapt. Los anuncios se basan tanto en datos de StackAdapt como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que StackAdapt haya recopilado de usted. Utilizamos los datos que suministramos a StackAdapt para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de StackAdapt
      The Trade Desk
      Utilizamos los servicios de The Trade Desk para mostrar publicidad digital en sitios respaldados por The Trade Desk. Los anuncios se basan tanto en datos de The Trade Desk como en datos de comportamiento que recopilamos mientras visita nuestros sitios. Los datos que recopilamos pueden incluir páginas que haya visitado, versiones de prueba que haya iniciado, vídeos que haya reproducido, compras que haya efectuado y su dirección IP o ID de dispositivo. Esta información puede combinarse con los datos que The Trade Desk haya recopilado de usted. Utilizamos los datos que suministramos a The Trade Desk para personalizar aún más su experiencia con la publicidad digital y mostrarle anuncios más relevantes. Política de privacidad de The Trade Desk
      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

      ¿Está seguro de que desea disfrutar de una experiencia limitada en Internet?

      Nos gustaría proporcionarle una experiencia óptima. Si selecciona “Sí” para las categorías que aparecían en la pantalla anterior, recopilaremos y utilizaremos sus datos para personalizar su experiencia y desarrollar mejores aplicaciones. Para cambiar su configuración en cualquier momento, consulte nuestra declaración de privacidad

      Su experiencia. Su elección.

      Nos importa su privacidad. Los datos que recopilamos nos ayudan a comprender la forma en que se usan nuestros productos, la información que le podría interesar y lo que podemos mejorar para que su interacción con Autodesk le resulte más provechosa.

      ¿Podemos recopilar y usar sus datos para adaptar su experiencia?

      Explore las ventajas de una experiencia personalizada mediante la administración de la configuración de privacidad de este sitio o visite nuestra Declaración de privacidad para conocer mejor las distintas opciones.