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Microsoft Power BI and AutoCAD Plant 3D: Improve Decisions with Data Visibility

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说明

Connecting Microsoft Power Bi to AutoCAD Plant 3D software enables your organization to apply business intelligence to your design models. Learn how to raise the visibility of the design process by giving project managers, engineers, and other teams access to your model data without interrupting the design process. Power BI can help answer questions like: What's the project progress in modeling? How many lines still need isometrics? Did all my equipment get modeled yet? Is my line list complete? These are common questions to ask, but they can require so much work to get an answer that the design process has to stop. With Power Bi, your reporting and project status information can be pulled in parallel with your design efforts. By being able to bring the status information to a weekly stand-up meeting, your team can focus on discussing solutions instead of discovering problems.

主要学习内容

  • Learn how to connect Power BI to AutoCAD Plant 3D SQLite or SQL Server databases
  • Learn how to navigate the AutoCAD Plant 3D data model
  • Learn how to create Model Dashboard
  • Learn how to view progress status of the design by comparing PnID lines to modeled and isometrics

讲师

  • David Wolfe
    David Wolfe started working in the piping design industry at Fagen Engineering LLC. While there, he implemented Intergraph CADWorx P&ID Professional software on a biodiesel project, and he utilized Intergraph CADWorx Plant Professional on some small ethanol projects. David continued his designer role with other biodiesel projects at Proformance Group Inc. Following those projects, David began working at ECAD, Inc., where he developed a Mastering CADWorx P&ID video series, taught at CADWorx & Analysis University, and became an active participant in Autodesk, Inc.’s, community forums. Throughout his work at these companies, David started learning programming first with LIST software, then Microsoft Visual Basic for Applications (VBA), and then moving on to .NET (C#). David teaches courses on AutoCAD Plant Design Suite software at the beginning, intermediate, and advanced levels. He also performs on-site consultations that help companies maximize their product use. David authored De-Mystifying AutoCAD Plant Isometrics and compiled Tailoring AutoCAD P&ID and AutoCAD Plant 3D.
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Transcript

DAVID WOLFE: Welcome to Power BI and Plant 3D-- improve decisions with data visibility. My name is David wolf. I'm the director of Plant technology services at applied software. We are overwhelming-- We are overwhelmingly blessed with data. And in data, to such a degree, we are shifting how we interact with the world to optimize our choice.

Newsfeeds, infinite scrolling, cycling articles, or cards by swiping up, left, right, or down, are all techniques used to try to help us make sense of the data available to us. Globally, we have started to realize that data without a purpose is essentially trash. We don't even bother checking the second page of search results unless we are really desperate.

This class sits at an intersection of many themes working themselves out in business and design worlds. Data first organizations are starting to shape long term thinking, businesses are becoming more scientific in their approach by developing rigorous frameworks to experiment and test ideas. Some of these ideas have been referenced and captured in the class notes.

Regardless of background or philosophy, let's set some groundwork to pick our path forward. Think back to the last project status meeting you had. Some of us are fortunate enough to work on projects where at least part of the studies have been completed before we start modeling. For those like that, perhaps your project manager asked you to prepare a status update on what's preventing piping from getting muddled.

Let's talk through what your experience might have been like. First, you probably go to the process engineer and make sure that you have the latest equipment list available. Then you'd go check with document control and see what drawings or revisions have been submitted over the last week, and make sure you have the latest copy of those. And then you would go through each list, cross-reference them, and make sure that you have captured the latest status for each item.

Conservatively, you spend at least an hour prepping for the status update meeting. Let's imagine a different alternative. We'll make some assumptions like most of the time the delay in modeling is due more to not having the right information to model yet, rather than time spent modeling. We would be able to pull a report in a few seconds that shows what's missing. With a few extra steps added to the configuration of plant 3D, the project manager wouldn't even have to ask you, because the vendor information will be listed, as well as a follow update.

That's the type of opportunity available by gearing up to provide more of a self-serve data environment. To get there, your business needs to focus on three things. First, build a culture. At every level in your organization, people need to start looking for ways to rely less on gut and intuition, and more on testing and information. Next, you need to understand your business structure.

Data needs to target specific roles and personas across the organization. Providing too much detail at the wrong level will frustrate people and make them question the validity of the data. Target roles and functions based on the questions that they ask on a daily basis. Third, socialized data use.

Start a grassroots effort, as well as efforts at the higher level to empower people from all areas to get on board. They want to look for small wins and build on those. Resources for this class are available in the download. And in those resources, we provided an in-depth guide and the write up for the class materials. We also have a Power BI sample file that demonstrates all the techniques shown in the PowerPoint.

We have also included a plant 3D project that corresponds with the power BI file. Let's talk about how you connect power BI to SQLite or SQL server databases. To refresh, SQL server is usually used on projects with multiple users for plant 3D. Most of the time if there are more than three to five people in your project, you'll need to switch to SQL server.

The reason for that is as pipers and designers input information, the amount of time required to save and the number of people saving drawings changes how the database can react. And so for those scenarios, you will need to move off a SQL light and use SQL Server. Most of the time when people implement SQL server, they use Windows credentials.

So when you're logging into power BI you'll be able to use Windows credentials as well. If you're looking for the database or the server name that you should use, you can find that information in plant 3D in the product setup window. The SQL server connection inside of power BI is native so you don't need any extra tools in order to connect.

Let's talk about SQLite. SQLite is typically used for local or single user Plant 3D projects. Now there is a little caveat. When you're using BIM 360, it also uses local SQLite databases, as well as vault. But with Vault you would connect directly to the SQL server. When you're using Power BI with Plant 3D, you'll have to install the skylight ODBC driver. And the instructions and steps for this are all captured in the hand out for the class.

The data model for both scenarios is the same between SQLite and SQL server. So all of the techniques demonstrated here will apply to both situations. Let's talk through the Plant 3D data model. It's important to understand how Plant 3D organizes and structures the information within the project. So that you can build the accurate dashboard that you need.

First of all, you need to understand what the role of PnPID is. When we go to Plant 3D, we'll take a look at the Data Manager and identify the PnPID in the Data Manager column. Here we can see it demonstrated that it's referencing a pipe. And so on the engineering items table, we could look at the ID 8955.

We're going to trace this pipe throughout the project and see how it relates with different tables. First of all, let's look at the PnP based table. Here under a PnP base at the bottom, you can see we found the row the PnP ID 8955. That corresponds to this row. When an item is created inside of Plant 3D, every item will have a record in the PnP based table. And so that controls how increments across all of the items and tables and operations within the project.

Next, we'll need to understand how relationships work. In this case, we're going to look at the P3D line group relationship. Our part, 8955, which is that pipe. Is within a certain line and we need to be able to associate that line in our reports. So in this case, we looked at the part ID 8955, which found the corresponding Lang group on the P3 D line part relationship table. And that's 5752.

And this is a little dry. But we'll get there. We'll get to building the picture. So when we look up on the three line group table, that part ID of 5752, gives us our size, speck, and number information and all of the rest of the data that applies to that line group. Last of all, you'll need to understand how to connect drawings to objects.

So our pipe 8955 is connected to a drawing. And the drawing in this case is 1P01. We can find this to the data links table. The data links table is a little bit different, because most of the time when we're looking for things, we're going to use the row ID column. The row ID column and the PnP data links table. Is the PnP ID column for all the parts, like engineering items or valves or whatever.

So here we'll look up the drawing ID, which is 4284. In order to find the drawing number, name in the PnP drawings table. Now, let's create a model dashboard. We're going to focus on building a process that's repeatable. In a normal design process, you would build a structural model first, then the equipment, and then the piping. In that process, the vendor information for equipment ends up stopping progress on piping design as designers wait for vendor information.

The outline for the equipment model dashboard looks like the following. And in our handout we have this listed out. So first of all, we're going to answer a question. The question is what equipment has not been modeled yet. This question is helpful because it fits in the larger context of asking is the project on schedule. When raising the discussion of risk dependency on third parties for information, is always a factor that has to be mitigated. Which is why we're asking these types of questions.

Next, we're going to select a metric. In this case, the metric we're going to use is the tags that are missing from models that are on Pn IDs. There are some guidelines you should be using as you pick metrics. First of all, like we just mentioned, you want to find the key question ask. Next, you'll have to apply some creativity to find some easy ways to measure and you might want to invest in automating the metric capture.

You'll san-- make sure you sanity check just in case things feel out of whack. In every metric needs to have a validation process if it's not automated. Don't be afraid also to approximate. We don't need it over engineering metrics. Close enough is good enough. Think of it as selecting a tolerance for the right tolerance. We don't build to the 64th of an inch because it would require us to overinvest in our tools.

So you need to make sure to select some good metrics. Last of all, not last of all. Next, we're going to develop a model. So this model is going to represent the information in our power BI that's going to be put into a chart. And when we're talking about modeling for power BI, we're not talking about a 3D model which we're used to. We're talking about data modeling.

So in this case though, all the information we're using is found within plant 3D. So our model is going to Shift a little bit to add columns like is modeled or is on a pn ID. But by and large, everything is there. Next, we'll create-- after the data model is done, we're going to create charts and graphics to create and customize the dashboard.

So let's get into it a little bit. So with regards to our data model and how we're going to build this. And the handout, the handouts can refer to the project equipment table. It's going to show us the items that have been set up in order to report the data. So here you can see at the far right, we have a model file name, which is used to capture the drawing number. And we use the PnP data links table relationship in order to find that.

We also have the Pn ID and the model. We also have added a column for modeled and on Pn ID. And so our modeled column is going to control whether or not the items have been placed. And the Pn ID column is going to show whether or not they're in the schematic. So here's what the dashboard can look like once we've defined that data structure within power BI.

On the left, we have the count of the model we're showing a percentage complete. And the model the key shows that is true or false for the model values. In the center, we have the number of tags that are not on the Pn ID, but are in the model. And so here you can see that the risk is greater, because we need to go back and input information into our Pn ID that got modeled.

Let's talk through the line design status. So another common question that we have is what's the status on the piping lines. Did we get everything modeled that's on the Pn ID. Where are we on ISOs. These are very common questions that they take a lot of time to figure out exactly where we are. So with a little bit of automation and integration into power BI we can answer those questions easily.

On the data model portion we did have to do some complex operations inside of power BI. So we did things like connecting the line number with the ISO style, and that enables us to get our ISO report. We also created a project lines table, which is going to summarize all of this for us. So we're going to use the line group ID, the Pn ID land group ID column, and the ISO count in order to reflect our design status.

And here we took a very simple approach. Just to set a basis for operations moving forward. We're choosing a design status of estimated. If a pipeline is only in the Pn ID or in the 3D model. And then if the line exists in both spots but it hasn't been ISO'd yet, the design status will be set to InDesign. Complete lines are lines that exist in the Pn ID, the model, and on the isometric.

So here is what our final output report would look like. And a couple of clicks just refreshing the data, we can get this report any time we need it. And so it gives us a much better ability to judge where we're at without having to go back and dig into information. Let's jump over to plant 3D and see some of these concepts in action.

All right. So let's review the SQLite database. Over here we can see our table of items and these corresponds to Data Manager. Which we'll look at in plant 3dD. Here's our PnP ID. And so we can go find anything we need on the PnP based table. Notice that on the left is where we have a view of all the items within the database.

So any item without a PnP at the end of it is a table. And you'll see the icons change. When you see the PnP that means that it's a query. And so our engineering items table is going to have a limited set of information. But if we look at the query for engineering items is going to put together the class name, the good, the timestamp, all of these first five properties come from the PnP based table.

So when we're selecting tables to bring into power BI, we're going to select these PnP table, the PnP views by default. Let's jump over and take a look at line group relationships. So this one isn't any different than the table. It just shows our line group and our part. And then here's the PnP data links. So we can review this and see these items. And so on.

So let's jump over to Plant 3D now. Over here in our Data Manager, you can see the PnP ID column. So this is the data record pointer that I'll let you know what part you're on. So by selecting this we can go through and find different items and correspond them back to a row in the database. Let's jump over to power BI and do a quick look at what that looks like.

So here's the report. And when we're using it we can come over here to our dashboard, and we can interrogate different parts of it. So I can right click. I can do show data points table. And it's going to give me the list of all the items that were included and the status. So there's a lot of complicated things we can do. We can format. We can do a lot of other powerful tools to let this work.

In the background, under relationships, we've gone through and defined the relationships between P3 land group. And the drawing links for piping, for between project equipment, based on tags, and engineering items, and other equipment. And so you'll be able to view all these relationships to see how they work together to function.

We also have under the Data tab, it can take a look at the project equipment table, which is the table created to generate our comparison between the model equipment and the items on the Pn ID. And you'll notice up at the top we have formula some similar to Excel. That build these columns for us. So you want to reference those as you look at the documentation.

Also, the project lines has columns defined for us. We can add or remove items as needed. And so we have formulas to show the steps for that process as well. Under-- Let me expand this a little bit. And under PnP drawings ISO is where the work has been done to correlate the ISO with the line number. And so at the far right, you'll see a line number column and then also the ISO style.

So that's the key contest behind creating dashboards with power BI, and using the Plant 3D data model to provide that information. All right. So let's do a quick review of the handout that you'll be provided with class. So we have the lessons learned. We have the business context and the resources list.

So you'll be able to get all the things you need to run through the sample provided. We also have the handout and the guide for accessing and using SQLite and SQL server. So these are step by step. We identify the tables that you'll need in order to create your data dashboard, and also some steps for switching the databases. Like to another project.

We also have detail around the data model, and how you can navigate it, and how they're put together, as well as the steps for creating the data model dashboard. Here are some guide around how to use and add items to your chart, and configuring that, as well as how to control your theme. And so out of the box your report's going to look something like this, but you can customize it using a palette designer, a color palette designer. Then also using a report theme generator to get the output that you want.

Last of all, we have the overall view and the steps for what we're used to create that. And some references for your notes in the future. Thank you for joining us for power BI and plant 3D. We're excited to see what you guys come up with when you build your dashboards for reporting against playing 3D data models.

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我们通过 Google Analytics (Strictly Necessary) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Strictly Necessary) 隐私政策
Typepad Stats
我们通过 Typepad Stats 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Typepad Stats 隐私政策
Geo Targetly
我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
SpeedCurve
我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
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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改善您的体验 – 使我们能够为您展示与您相关的内容

Google Optimize
我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
ClickTale
我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
OneSignal
我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
Optimizely
我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
Amplitude
我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
Snowplow
我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
UserVoice
我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
Clearbit
Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
YouTube
YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

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定制您的广告 – 允许我们为您提供针对性的广告

Adobe Analytics
我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
Google Analytics (Web Analytics)
我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
AdWords
我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
Marketo
我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
Doubleclick
我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
HubSpot
我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
Twitter
我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
Facebook
我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
LinkedIn
我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
Yahoo! Japan
我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
Naver
我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
Quantcast
我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
Call Tracking
我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
Wunderkind
我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
ADC Media
我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
AgrantSEM
我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
Bidtellect
我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
Bing
我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
G2Crowd
我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
NMPI Display
我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
VK
我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
Adobe Target
我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
Google Analytics (Advertising)
我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
Trendkite
我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
Hotjar
我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
6 Sense
我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
Terminus
我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
StackAdapt
我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
The Trade Desk
我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
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

是否确定要简化联机体验?

我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

个性化您的体验,选择由您来做。

我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。