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Hi, Sudheer.Thank you for your question, and fantastic to hear you are using the GraphQL endpoint, and creating queries using natural language. This is a powerful way of using generative AI and the knowledge graph in Cognite Data Fusion.The endpoints powering Cognite Data Fusions Generative AI capabilities are unfortunately not available for custom app development at this time. You will need to setup your own integration. Best of luck with your application, and post questions here if you need guidance. Best regards,Knut J. Vidvei
Hi, Cristian. Yes, the status reflects that there is implemented a way to achieve the user goal. (Option B). We do of course take this valuable feedback in to our continous improvement in user execution to make all user flows as intuitive and helpful as possible. We'll keep this thread open and and keep the conversation and input open. Thank you for your continued feedback, and making the product even better. Best regards Knut Vidvei
Gathering Interest→Implemented
Hello, Vetle.Thank you for a great question. The value of this functionality is that you can download calculations built in one chart and upload the same calculations for re-use in another chart.This means you can quickly scale if you want to run the same calculations for different processes. Or to share best practices across teams, since you can share these files with co-workers.Go to the Action button in the top right corner:Actions … → Download Chart → CalculationsTip; It’s a good idea to rename this file to reflect which calculations it contains. To upload go to the chart you want to import the calculations to → Blue (+) button → Import calculations → Select the JSON-file Note that all calculations in a chart will be included when you download. Also, the source time series as input to the calculations is not included. This means you can add these from the dropdown in the “Source” nodes in the calculations in the new chart to run them with new data. Best regardsKnut
Hi, CristianGreat feedback on the experience when adding nodes to the calculation. We take this valuable feedback into our product team.Can I ask if you are adding new nodes using theblue “+ Add node” button in top right corner Right-clicking where you want to add the node.The reason I ask is that if you add nodes using option B, then the new node will appear exactly where you want it. See the difference in the two patterns below. Best regardsKnut Vidvei
Hi, Vamsi.Thank you for raising the question. The default mode for Charts is to fetch the data using an automatic granularity calculation based on the number of datapoints that is requested when you select a time frame. It is not locked to how many minutes, days, weeks or years you are looking at, but how many data points it will load.The logic aims to load as much representative data as possible, while still optimizing for performance in the front end so you can easily move between different time scales with high performance. If possible it will load all the raw data points, and you will see the line plot add dots where there are data points when this transition happens.We have been looking into ways for the user to control the granularity for each time series individually, but the current state is that this is set to “best fit” by the application.Let us know your thoughts and your usage patterns you want to achieve. Best regards, Knut
Hi, Vishnu. Right now there is not a way to link a specific Chart to an asset that shows up as links in 3D.We are working on better ways to show where things are “used in” to show up as a tab, but timeline is not clear. I will post an update here if we have a development in this area.Thank you again for your questions and interest in Cognite Data Fusion. Best regardsKnut
Hello, This issue has been resolved, and the updated and latest Grafana plug-in (4.0.1) is available.Grafana data source: https://grafana.com/grafana/plugins/cognitedata-datasource/ Docs: https://docs.cognite.com/cdf/dashboards/guides/grafana/getting_started/ Best regards Knut
Hello, Vishnu.Thank you for the detailed description, and your enthusiasm for Cognite Data Fusion and Charts. In order to understand better how to assist you here, may I ask some follow-up questions? First on comparing predicted data in a data model against actual sensor data, where is your predictive model running? If it is e.g. a Python model running on your local computer you could use Cognite Functions to run your Python code on demand or on a schedule. In your code you could then create a calculated time series with an externalID that can then be visualized in Charts. Read more about Cognite Functions in our documentation here: https://docs.cognite.com/cdf/functions/ and an online training course in Cognite Academy: https://learn.cognite.com/path/data-scientist-basics/cognite-functions If you are working with Python and Cognite Data Fusion you are probably already working with: https://developer.cognite.com/sdks/python/ and you have reference code for creating and updating calcula
Hi,I zoomed in and highlighted the option with a red box here:
Using Python code and InDSL you will have the full freedom to customize your views. These preferences will vary from user to user, and customer to customer.However, you can still do a lot in the fronted. if you use the visualization setting in the outlier detection time series, and set Type to “none”, it will show the dots as you have in your Python plot above. I scaled here the y-axis so that the results with 0 is below the view line.Allowing full flexibility as you have in Python in a no-code frontend is a bigger challenge, as it would lead to an unmanageable number of settings and buttons.
Hi,The outlier detection gives you a new time series that based on your settings calculates whether the data points in the source time series are outliers or not.The new time series will be 0 if no outliers are found and 1 if there are outliers that match your input settings. If you want to go deeper, and see Python code and examples using the underlying Industrial Data Science Library you can also see details here:https://indsl.docs.cognite.com/auto_examples/data_quality/plot_out_of_range.html Knut
Hello,This is a great question. You have two options based on if you need to evaluate historic thresholds, or be alerted on future thresholds.Future thresholds. In the right hand menu, choose Monitoring and create a monitoring-job to evaluate the threshold for future incoming data. You will receive an email when it is breached, and alerts are available in Charts under menu “Alerts” Historic threshold breaches. Use the right hand menu “Thresholds”, and select Over or Under or Between. The breaches and the total duration is shown. It is however not “flagged” or highlighted in the Chart beyond showing the threshold line as if now.Knut
Hi, is this 137 different Charts, or 137 different calculations?While we do not have SDK functionality to create charts and no-code calculations, two options are either code or no code option. no code calculations ca be downloaded as JSON file to your computer (top right menu … and download calculation). This JSON file can be uploaded to any chart so you don't have to recreate it. Just assign the right time series in the new chat. Run the calculations as Python code using Cognite Functions, and automate the calculations. The resulting time series can be opened in Charts.
Hi, Marcela. Thank you for this feedback. I understand that when you need to delete a larger volume of tags it is a bit cumbersome. I'll set this idea to gathering interest, and we'll look at ways of making it better. Cc @Magdalena Rut @Arun Arunachalam Best regards, Knut
Hello, Michael.Thank you for your interest in contributing to InDSL. Let’s connect through our partner channels and discuss some options. Best regardsKnut J. Vidvei
Hello, Christian.Perhaps this will help. We have a logical check function that might help here.Perform a logical check between time series/constants and returns the assigned time series/constants when the condition holds true or false. The logical check is performed following the format: Value 1 {operator} Value 2, where the operator can be Equality (==), Inequality (!=), Greater than (>), Greater or equal than (>=), Smaller than (<) or Smaller or equal than (<=) Here is an example of it being used: Best regards, Knut
New→Gathering Interest
Hi Ram.Thank you for this product proposal! We fully understand the need to organize charts in folders once you get to a higher volume of charts to get an overview.Leaving it here for others to add their thoughts and comments!Knut
@rsiddha thank you for adding your experience here. We have someone looking into this and will get back once we know more. Knut
Hi,We have been building native monitoring and alerting services into Cognite Data Fusion, and would like to get in touch on this topic. Based on your needs, we can set this up for testing. CC @Arun Arunachalam
Hi, @rmaidla Quick question, do you have to clear cache every single time or once in a while? Knut
Hello, Richard.Thank you for reporting this. You should not need to clear your cache to load here. Let us investigate and reach out directly to fix this nuisance. Best regardsKnut
Thank you for sharing the perspective from Celanese as well, @rsiddha! @Peter Quinn We greatly appreciate the active and open participation of our customers and partners in sharing their valuable insights and feature requests within our community. This allows us to gather perspectives and understand the diverse needs of our user base, and helping us building better products.In addition we would also be more than happy to arrange a separate meeting to discuss this topic in a more private setting. Please reach out to your Cognite contact person to arrange this.We are excited about the potential of your suggestion and look forward to hearing more from you. Knut
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