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Make sure not to miss Cognite Application Developer Session at 4PM CEST/10AM EST May 10th! From simple multiple data source dashboards to cutting-edge hybrid AI solutions, join us for this one hour and learn how Cognite Data Fusion makes industrial application development easier.Watch recording:     

Hi community!I got a query from our customer that they’d like to control the float precision in Chart.I found “Round” function in “Operators” and confirmed applying that indsl to the timeseries data does work.But I’d like to ask if there is any other, easier, way because creating function per every timeseries data is a bit boring.Thanks!

Hi,Is possible to make a sql query to an external SQL server from a Cognite Function? 

Can the default option be that the week start on a Monday, or maybe give the user the ability to say what day is the first day of the week? This probably varies in different parts of the world. Where I work and live and do things; Monday is always the first day of the week :). 

Only a fool believes in different outcomes by doing the same as before.The modern data stack - a more nuanced view of data platforms - is quickly gaining ground, focusing on making data truly useful, not just storing it in the cloud. Modern data stack based platforms are the only means of moving beyond costly, monolithic, closed business applications that maintain business and data silos, preventing real digital transformation.Platforms themselves are equally no longer monolithic products, but equally composed of interoperable platforms services from multiple open platforms. Open platforms with composable business applications are the new technology imperative. Old technology stacks, and “lets only focus on the discrete business solution at hand” approaches don’t work for the 2020s enterprise.OT, IT, and business must work together to prevent tug of wars - and instead - collaborate to secure competitiveness in the new platforms era.Read the full article:  Did this article cause some re

Only a fool believes in different outcomes by doing the same as before.Executive summary: The modern data stack - a more nuanced view of data platforms - is quickly gaining ground, focusing on making data truly useful, not just storing it in the cloud Modern data stack based platforms (simply referred to as 'platforms' from hereon) are the only means of moving beyond costly, monolithic, closed business applications that maintain business and data silos, preventing real digital transformation Platforms themselves are equally no longer monolithic products, but equally composed of interoperable platforms services from multiple open platforms Open platforms with composable business applications are the new technology imperative. Old technology stacks, and “lets only focus on the discrete business solution at hand” approaches don’t work for the 2020s enterprise OT, IT, and business must work together to prevent tug of wars - and instead - collaborate to secure competitiveness in the

Hi, Both a colleague of mine and I keep getting the following message for the first 10-30 seconds when we try to view the list of public charts :  “Could not load chartsFirebasError: {code=permission-denied]: Missing or insufficient permissions.”After some time, the list of public charts appear. This time interval can vary between a few seconds and up to over a minute. Other colleagues of us are not experiencing this issue.  It seems strange that the error only occurs for a short time, but it reappears every time we try to open public charts. We have tried deleting all cookies in the web browser without this affecting the issue. Do you have any clue what could cause this? 

Two of the important goals with a Data Mesh Architecture would be:Ensure that the users of data can easily find and trust the data – through carefully consider distribution of ownership and governance throughout the company/domains Ensure that data is “interoperable” across domains – to understand the meaning of data from one domain in the context of another domain.Question: What are the challenges and advantages of a Data Mesh Architecture to achieve these goals? E.g.:Domain expert knowledge and capacity within the business area/domain vs centralized knowledge Ability to make data interoperable across domains vs all-inclusive master data management Make it easier for end users to make use of the data Change management – move towards a distributed data ownership model where ownership is understood and prioritized day-to-day.Other thoughts? 👀

H! Here’s the latest and a quick read on our compliance: Cognite’s Management System (QMS and ISMS) is ISO 9001 and ISO 27001 certified Cognite and CDF operation and data processing are in compliance with GDPR Cognite has obtained SOC 2® type II certificationRead more 

Hi! Here's an update and some quick reads on our Compliance:Cognite’s Management System (QMS and ISMS) is ISO 9001 and ISO 27001 certified Cognite and CDF operation and data processing are in compliance with GDPR Cognite has obtained SOC 2® type II certificationRead more 

Since Cognite's start, we have prioritized security and take our security role very seriously as a partner to mission-critical industries. Today, I am happy to announce that Cognite has obtained our SOC 2 Type II certification. The American Institute of Certified Public Accountants (AICPA) bases SOC 2 engagements on its Trust Service Criteria. These criteria ensure we have rigorous security guidelines and stick with them. Type II certifications, in particular, are comprehensive and involve significant work to prepare, so a huge thank you to our team and our partners for their contribution to this achievement. At Cognite, we are investing in more automated ways to support continuous compliance monitoring.  We focus on empowering our end users with industrial data operations without managing the related infrastructure. We believe it's our mission to create frictionless security, and our SOC 2 Type II certification is another significant step toward this mission!

Currently when fetching datapoints from multiple timeseries, the Python Cognite-SDK splits up the requests into one request per timeseries, while the underlying CDF API supports up to 100 timeseries per requests. This slows down fetching multiple timeseries, which is a problem when you display multiple timeseries (or aggregated of timeseries) in a frontend application. 

Cognite Summit 28.04.22: Industrial data operations: Data as an asset. Presentation by Cognite.

The below is reflecting current thinking from the App Dev Journey team in Cognite and is a mental model that will likely develop over time as this topic mature.A data model enables users to customize the shape and structure their expectation of data. It plays a crucial part in building solutions (like data science models, mobile and web apps). It is also the core of an ontology, knowledge graphs, or industry standard.There are some crucial reasons why data models are effective for the industrial space. Data modeling enables explicit language, flexible customization, governed iteration, and enhanced accessibility towards data. Let's dive further into each of these qualities of data modeling. Data Model is Explicit​A data model needs to be explicit because it provides a clear contract/interface between data providers and consumers. Hence, those loading the data and using the data can both understand the underlying data and use it correctly. By having explicit data modeling, a shared cont

This presentation gives a quick introduction to Cognite as a company and our core product, Cognite Data Fusion.  Get introduced to how our products turn industrial data into customer value by liberating it, contextualizing it, and making it actionable for users.

I was thinking around the idea of adding the bindings and mappings into the Solution Data Model as directives to have more simpler syntax and UX. The idea is to “hide” the data model storage syntax and bindings syntax so everything can be merged into Solution Data Model GraphQL SDL.For example if we have following Solution data model type Person @view { firstName: string lastName: string}The following DMS should be automatically created Data model storage-----PersonTablefirstName: stringlastName: string However, if I want to make some overrides, I can use the additional directives. For example: type Activity @view @bind(filter: { hasData: { "in": "Risk" } }) { position: string @bind("dms.Table2.position") action: string line: Asset @bind("dms.Asset") equipment: Asset}In this case, in DMS, the Activity data model can be created automatically as well as the bindings and mappings to the related tables.Thoughts?

Hey, Currently, it’s hard to maintain a coherent versioned datamodel in CDF. With Templates, and further developments there, this becomes easier.Even with a versioned datamodel it seems to me that there still isn’t a good way to track changes in the model that are not version-breaking.In our datamodel we have two types of changes that we would like to track in a structured way: Field value updates, as simple as a metadata field and as complex as the unit-multiplier on a TimeSeries changing. Edge field value updates. Our model is  an adption of a RDF representation of  a Common Information Model in the Common Grid Model Exchange Specification for Norway. A field on an object can imply an edge in the datamodel, and this field can change. Currently this is solvable with  Labels and Start/End time on Relationships today, though it isn’t obvious that we would want to introduce an Edge type to Templates?This question is a part of the larger struggle of maintaining a sane structure on a time-

Introduction In this post we share some of our internal material aimed towards solution builders, such as data scientists, who want to develop their ability to develop high quality solutions by creating more reliable, maintainable and readable code. This is the first part of 2.MotivationHigh code quality is easy to recognize but can be very hard to describe concretely. The assumed benefits are easier maintainability, modifiability, and more. While code style, like formatting, can be a matter of different taste, most parties agree that other code practices that fall under the umbrella term “anti-patterns” should be avoided. To stop endless formatting discussions and the like, having (and adhering to the industry) standard makes reading and understanding code across repositories easier.What this guide is notThis guide will not tackle the topic of  “how to set up a Python project” the right way . Please let us know in the comments if you would like us to share more of our experience in t

Hi,If you are to share a chart today, you have to share it with everyone. Are there any plans for making it possible to share it with a specific group? The reason for asking is that we have a project that is interested in using charts, but they only want to share their charts with their own users. Ola

We are currently migrating to OIDC where we need to give access through access groups linked to Azure AD.On our Statnett cluster it seems that a user needs to explicitly be member of a group “transformations” in order to to delete (or edit) a transformation.The admin group has the capabilities  (on “test”) {'transformationsAcl': {'actions': ['READ', 'WRITE'], 'scope': {'all': {}}}}]But we need to login to the legacy login without OIDC and have a service account linked explicitly to the group “transformations” in order to delete a transformation. The group “transformations” has no capabilities set.I have tried both Fusion and the API/python-SDK (read is possible):CogniteAPIError: Transformation not found. This may also be due to insufficient access rights. | code: 403 | X-Request-ID: b7c0beb6-d3e0-9ec4-ba50-895533ac1996

 Hi! I’m Dilini Fernando from Cognite! This is my first post, and I am super excited to share a how to guide on Cognite’s DB extractor. This post is targeted to folks who have not used the DB extractor before and wish to extract data from popular tabular databases like MySQL, Oracle, and PostgreSQL databases and ingest it to CDF.The post contains three major steps. The first two focus on setting up a database and ODBC driver, and the third step focuses on running the Cognite DB extractor. You could skip steps that are not required for you. For example, if you already have a database setup, you could skip the first step. Step 1: Setting up a databaseDownload Micorosoft SQL Server Express Edition 2019Install the server Note: Remember the password.  You need to enter the password when you are login to SQL Server Install SQL Server Management Studio. Connect SQL Server Management with SQL server 2019.    Open SQL Server Management and select the Authentication as SQL Server Authentication.

Hello everyone,I was curious if anyone has leveraged Cognite AIR (Automated Identification and Reporting) in a way where alerts could be triggered off of other alerts? If so, how has this been done?I’d like for this to be a core feature of AIR where you can build a workflow from a visual canvas (similar to the charts function builder) and say “If this alert is triggered, check if this other alert has been triggered also” and so on. This would allow for setting up “offline conditions” so we don’t see all anomaly alerts or threshold alerts unless we can confirm the equipment is running, or even automate root cause investigations. Currently if I build an alert, I’m getting too many “false positives” of sorts that I’d like to filter out. Any input is welcome. Thank you,Richard Maidla (Hess Corporation)

At release, will Schema Services support being federated into a GraphQL schema, like with Hot Chocolate or Apollo?  This is how we are planning to utilize combining what is available in CDF with what we are providing in our GraphQL schemas and I was assuming this is feasible.  But, a dev mentioned that the downstream services have to support being federated for it to be made available at the federation gateway. If you are using Lighthouse for your implementation, then I see it has preview support for being federated, but I need to confirm you will configure it this way or whatever you may be using will support being federated. Thanks!

Hello!We have a new version of the new documentation around Templates out live on our Documentation portal!https://docs.cognite.com/dev/concepts/resource_types/templates/Here we provide a full guide on how to go from modeling the data to querying the data. As well, we provide much more detailed specifications on what is doable via the UI and also the SDKs.Please provide feedback on what else you would like to see documented and if you run into any issues with the code samples / guides!

As an application developer, a very common interface to build is filtering user interfaces. There are a few types of aggregation that would be very useful to us! #1 Unique value aggregationIn order to allow for effective filtering, aggregating a field by all its unique values is vital for this, to enable showing the user all possible options for a certain filter.Generally the amount of results can be limited to perhaps 1000, but having this paginate (or a higher number of 10000) would be even better! This also allows us in many cases to avoid needing expensive ‘substring queries’ on fields, as doing this in the front end on several thousand strings is trivial. Not all fields needs this, so if its required to add a `@aggregatable` decorator, then this is fine!In addition to this, having the amount of each of these values would be useful, to allow us to sort by the most commonly occurring fields.This is by far the highest priority for our use case! #2 Count aggregationSecond most importa