# Getting started with data sets

Data sets let you document and track data lineage, ensure data integrity, and allow 3rd parties to write their insights securely back to your Cognite Data Fusion (CDF) project.

Learn more about data sets:

Create and edit data sets:

# What is a data set?

Data sets group and track data by its source. For example, a data set can contain all work orders originating from SAP, or the output data from a 3rd party partner's machine learning model. Typically, organizations have one data set for each of its data ingestion pipelines in CDF.

Example data sets

A data set is a container for data objects and has metadata with information about the data it contains. For example, you can use the data set metadata to document who is responsible for the data, upload documentation files, describe the data lineage, and so on. Data sets are represented in CDF as a separate resource type with a /datasets API endpoint.

To define which data objects, for example events, files, and time series, belong to a data set, you specify the relevant dataSetId field for each data object. This is typically done programmatically in the data ingestion pipelines. Data objects can belong to only one data set so that you can unambiguously trace the data lineage for each data object.

You can organize the following resource types into data sets:

  • Assets
  • Events
  • Files
  • Time series
  • Sequences

Learn more about resource types in the CDF data model.

# Why data sets?

For proper data governance, users need to be able to trace the data lineage to understand where data originates from and be confident that the data is reliable. Data managers need to ensure data integrity and to let 3rd parties write data back to CDF.

# Trace data lineage

  • IT managers need to know which data is currently available in their CDF project.
  • Data scientists need to know if they can rely on the input data for the use cases they're solving, and who to contact if they need more information.
  • IT support staff need to know how the data is integrated to help troubleshoot any issues.

# Ensure data integrity

  • When data engineers and IT managers have designed, implemented, and approved the data ingestion pipelines, they need to protect the pipelines from accidental changes to keep the data valid and accurate.

# Let 3rd parties write data securely back to CDF

  • When you want 3rd parties to write their insights back to your CDF project, you need to provide a safe container to hold their data and, at the same time, safeguard data from your other data pipelines.

# Data set concepts

# Write-protection

We recommend that you write-protect data sets that contain production-critical data to preserve the integrity of the data.

Only members of groups that you explicitly grant access, can write data to a write-protected data set. Other users, apps or services can not change the data in the data set even if they have the necessary access rights to change the data objects contained in the data set.

To write-protect a data set:

  1. Create or edit a data set and mark it as write protected.

  2. In access management, use the datasets capability to set the owner action for a group and scope it to the dataSetId.

    Desired access Capability Action Scope
    Write to a specific write-protected data set datasets owner dataSetId

# Governance status

Set the governance status to define if the data set is Governed or Ungoverned.

  • Governed data sets have a designated owner and follows the governance processes for data in your organization.

  • Ungoverned data sets indicate to users that the data may not be reliable. If you want to use data from an ungoverned data set, we recommend that you first contact the owner or creator of the data set to learn more about the data.

# Labels

Use labels to make data sets more discoverable, and to group similar data sets. For example, you can use labels to specify the type of data it contains, the geographical region covered by the data, or which business unit uses the data. You can search for data sets by their labels.

# Archiving

You can archive data sets to hide them from the Fusion UI and make the data set unavailable to users. The data set and the data it contains is not deleted, and you can always restore archived data sets later.

# Lineage

Data lineage helps you be confident that the data in a data set is reliable. On the lineage tab for a each data set you can see who has created a data set, where the data comes from, and how the data has been processed. Data lineage to understand where data originates from.

You can provide information about the lineage when you create or edit the data set.

Last Updated: 5/3/2021, 11:59:35 AM