Community Discussions

Hello Team,I have a modeling question.We want to add some well information to all object types in our knowledge graph. At the same time, we don't want to create a link from the objects to the well.So, to avoid data duplication and updating these pieces of information, I thought about using the mapping functionality.For example, I have a casing object with two attributes: name and diameter. And I added a name_well attribute using the mapping functionality, which, as I understand, under the hood, performs a join.type Well { name: String}type Casing { name: String name_well: String @mapping(container: "Well", property: "name") diameter: Float32}Well transformation:select wh.IDWELL as externalId, wh.WELLNAME as namefrom well-data as whCasing transformationselect cas.IDCASING AS externalId, cas.NAME AS name, cas.DIAMETER as diameter, wh.WELLNAME as name_wellfrom casing-data as cas join well-data as wh on cas.IDWELL == cas.IDWELLWhat I don’t understand is how exactly this join i

can someone please explain the this procedure for me with details ? because I got really confused. so first we register an app  and create a client secret and add api read all permission n Microsoft azure, after that we create an app in SharePoint  and we add the “permission request” to it later. after that what is next before downloading the extractor ? how are the two apps linked ? I saw someone at my work using Microsoft graph to link them but did not understand the logic behind it. and if this how they are linked , how ?  when in the Microsoft when doing the post each app dose not mention the other  

I am starting the Cognite Data Engineer Learning Path. How to get the access to Cognite Data Fusion platform to practice the learning.

The new CDF Power BI REST connector has been certified by Microsoft and is now included in the latest Power BI desktop version and deployed in the Power BI online service.What's new with the Power BI REST connector:Flexible authentication: Connect Power BI with any IdP supported by CDF (the legacy OData connector only worked with Azure Entra ID) Broader data access: Fetch data from OData services (just like the legacy connector) Access data from Data Models using GraphQL Connect to any GA CDF API endpoint Significant performance boost: Up to 10x faster when using regular REST endpoints compared to fetching the same data via ODataThe connector is currently in Beta, and we're eager to hear customer feedback before promoting it to GA. The documentation for the new connector is available here, and we're working on a new set of micro learning modules in Academy based on the new connector.

In Open Industrial Data (OID), we have moved away from API keys. Open Industrial Data currently supports Open ID connect. You can check out more on how to configure OpenID Connect on Open Industrial Data.If you are planning to use OID and authenticate using client credentials flow, you will need a client secret from the app registration on the Azure Active Directory. Go to Open Industrial Data and you will observe there is a widget for generating a new client secret IDIn the drop down, you can select two options:Other: Use this if you are using Postman or Python SDK Javascript: Select this option if your app is in JavascriptOnce you click on Create client secret, this will be display just once. Make sure to save it somewhere safe.Let me know if you have any questions 🙂

Is anyone using Cognite as their main timeseries historian? We are always exploring alternatives and would be interested to hear if Cognite has fit this use case for any users. 

Here are the features and functionalities that you can expect to find in Industrial Canvas as of June release:Work with several related data types:You can search and add the data you need in the canvas such as files, images, time series, assets, events. Use the button “Add data”. When adding P&IDs to the canvas, each highlighted area is clickable and can be used to add additional data to the canvas. Add personal files and images from your local machine by just using drag-and-drop. You can also add data to the canvas while being in Data Explorer, in Cognite Data Fusion by clicking on “Open in Industrial Canvas”.Add related data directly from the data already selected in the canvas  User interactivity:Create/Rename/Delete a canvas. Free form experience, canvas-like experience. You have access to different shapes, text box, sticky notes and connected lines. Easily add insights on top of selected data.Collaborate with your peers:Share the canvas with your colleagues by either sharing t

I have changed phones and am not able to setup Microsoft authenticator on the new one.Please reset the MFA Access so that I can set up the authenticator again.

I was fetching data using token.I am encountering a CogniteProjectAccessError while fetching data:"You don't have access to the requested CDF project='**' | Code: 401 | X-Request-ID: 6530e2ad-ff30-9d91-af29-218a4c3c0e62 | Cluster: **"

Hello Developer Community,The Contextualization team at Cognite released an experimental interactive engineering diagram flow on fusion.cognite.com  . The old interactive engineering diagram flow still exists in fusion.cognite.com, however, it will be replaced with the new flow come August 1st. Thus, we highly encourage you to try out the new flow titled Explore and create interactive engineering diagrams. This new flow includes a plethora of new functionality and updates such as: Overview of all interactive diagrams in fusion.cognite.com  Easy test setup for relevant file and asset links Handling 1000 engineering diagrams in one go  New P&ID preview component Reducing and cleaning up technical debtAgain, we are still at the experimental stage, so any feedback we receive is beneficial to future iterations and to truly polish the interactive engineering diagrams flow. Please provide any feedback to the Contextualization Cognite hub group found here .   

Pygen v1 is now released and ready for use. This means there will be no more breaking changes of pygen, and it can be used in production. 

When we create a custom model which implements a few core concepts and features from CDM such as CogniteDescribable & CogniteAsset, the GraphQL shows these errors - "Unknown type "CogniteAsset"", "Unknown type "Cognite3DObject"". The Query Explorer also shows the errors as below:These errors were not at all expected since we are not even using “3DObject and other things”. To resolve this, we were suggested a workaround to add every core concepts and features in CDM as views into our data model.It did resolve the above errors, but results in all the CDM views being added to my model, majority of which I am not using.Two things about this:1) Does not feel correct to add all the CDM views into my model to remove these errors, we should only need to add the views that we are going to implement.2) I don't want to see all these additional views that are not being used even. Any suggestions? Anyone?

I see that the API is updated with AI capabilities for documents. We tried that on some PDFs, and worked nicely. However, I have a particular PDF, which seems to be a scanned version, and the API is not able to read that. I am trying to convert the file to text, but the vision API only supports jpg and png files. Do you know if it is possible to convert pdfs to text somehow using the Cognite libraries (for instance contextualization)? Any ideas?

A few highlightsSupport for filtering on direct relations in the .select method. The .select method is no longer in alpha. When calling .upsert pygen detects fields explicitly set to None and writes it to CDF. The .retrieve() method now (like .list()) have the retrieve_connections parameter to retrieve connections.Full changelog.

Hello team, I am trying to get the details of a reverse direct relation from my data model. In the SDK documentation I found some sdk methods. I have tried client.data_modeling.views.ReverseDirectRelation(source= "Entity", through="entityType") but I am getting the error that ReverseDirectRelation is not found in views could you please tell me what SDK method I should use to retrieve information on ReverseDirectRelations from my models.

HelloI was thinking Congite should create a comprehensive guide on best practices for a 3D walkthrough to enhance user experience and efficiency. Navigating 360 images,getting the best point cloud performance, and mixing in CAD models while leveraging the platform's full functionality can be a bit overwhelming with numerous buttons and features to explore. A detailed guide would streamline the process, providing clear instructions on entering and exiting 360 views, highlighting essential tools, and showcasing advanced features. This would empower users to make the most of the 3D walkthrough capabilities, reduce learning curves, and ensure consistent, optimal usage across teams.

Hi Everyone,I need to create query like it is creating on cognite UI’s  like   { "listEntity": { "with": { "0": { "limit": 50, "nodes": { "filter": { "and": [ { "matchAll": {} }, { "hasData": [ { "type": "view", "space": "slb-pdm-dm-governed", "externalId": "Entity", "version": "1_7" } ] }, { "or": [ { "and": [ { "nested": { "scope": [ "slb-pdm-dm-governed", "Entity/1_7", "parent" ],

Hello Community,The Records and Streams APIs are now available for early adoption, with an expected announcement of Beta software maturity level in January 2025. Intended use cases for Records are the storage of high volumes of structured data such as Logs (i.e. Alarms and Events, Manufacturing Logs and Well Logs), and Historic Data.  The API is designed to handle hundreds of billions records per year, from various source systems.  Use cases that currently store historic data as Nodes in the industrial knowledge graph are excellent candidates for the use of the new API.Early adoption means Cognite provides you access to pre-production APIs (and later SDKs) in return for engagement and feedback during the product development process.  By default, the APIs are not enabled in every customer project.Early adoption intended to provide those customers who are interested in utilising the API functionality in their future plans, the ability to gain an understanding of the product concepts, pro

@Tanmay Deshpande and @Tom Jonsthovel , posting your question here to make it easier to engage the developer team for support. We have successfully created the ILA group and can call the API, however we currently get stuck on ingesting logs (400 - bad request). Please see our steps below.  It would be great if you could advise on how to properly ingest logs and share a Jupyter notebook with some examples. Also, would be great to understand the link between the ingested log and the container. Eg, do we need to add a 'log' property to the container definition?Created a data model. Ingest a log into the container with externalId "Pump" and link to "Pump" instance with externalId "66470bf0-5c07-4a39-8878-0adf4dc7f448"Get 400 on return. 

Hi Everyone,I’m reaching out to the community to gather valuable feedback and insights on Cognite Data Fusion (CDF), specifically its Canvas + Charts features as applied to Root Cause Analysis (RCA).How are these tools impacting the RCA process? In your experience, how have the quality, dependability, and response time of RCA processes improved since implementing CDF? What kind of improvements have you observed in identifying root causes, especially in terms of speed and accuracy? With the inclusion of Generative AI (GenAI) within CDF, how has AI-driven data exploration changed your RCA workflows?I’d greatly appreciate hearing about how the combination of Canvas, Charts, and GenAI is transforming the way you approach RCA, and any real-world examples or challenges you’ve faced.Looking forward to your insights!RegardsMuhammad Waqas 

A chart in Canvas should update if it is changed in Charts. For example, I added a Chart to my Canvas. Then I added another timeseries to my Chart. But in Canvas, the chart didn’t update with the new timeseries. 

I am trying to update column value in view using upsert method, but it's not working and giving 400 error code.  adding screenshot of upsert api, as its not matching with the input structure provided in document.

Hi there,Before I begin, some terminology to make sure we are on the same page.CDF tenant = CDF project (these have been used interchangeably over time, not sure which is applicable at the moment, I will be referring to it as tenant)CDF cluster = The cloud cluster where the CDF tenants/projects/instances are hostedNow, let’s begin.At Aker BP we have been migrating over to a dedicated CDF cluster on Azure and we have been experiencing some pain points with regards to the compute resources being shared for all tenants on the cluster. Previously our CDF tenants were hosted on GCP on a cluster shared with other companies, this cluster is scaled to handle multiple customers and so the base scaling of the compute resources is much higher than it would be on a dedicated cluster, and as such these problems are less likely to be encountered, not impossible just not as likely. The problem we have seen is that if we from our dev tenant overload the API then the API becomes unavailable for all our

OEM’s are focusing on performance based contracts but are lacking information about their installed assets . It’s important to create a data foundation to map all assets . How does Cognite provide solutions ,is it by integrating with SAP /Maximo ?

Hello,As per your documentation for the SkipState behaviour:'In case of failures, retries will be performed until exhausted, after which the task is marked as FAILED and the Workflow is marked the same. In the event of a timeout, no retries are undertaken; the task is marked as TIMED_OUT and the Workflow is marked as FAILED.'But this is not what happens: