Profile your data
This document explains how to use data profile scans to better understand your data. BigQuery uses Dataplex Universal Catalog to analyze the statistical characteristics of your data, such as average values, unique values, and maximum values. Dataplex Universal Catalog also uses this information to recommend rules for data quality checks.
For more information about data profiling, see About data profiling.
Before you begin
Enable the Dataplex API.
Roles required to enable APIs
To enable APIs, you need the Service Usage Admin IAM
role (roles/serviceusage.serviceUsageAdmin), which
contains the serviceusage.services.enable permission. Learn how to grant
roles.
Required roles
To get the permissions that you need to create and manage data profile scans, ask your administrator to grant you the following IAM roles on your resource such as the project or table:
-
To create, run, update, and delete data profile scans:
Dataplex DataScan Editor (
roles/dataplex.dataScanEditor) role on the project containing the data scan. -
To allow Dataplex Universal Catalog to run data profile scans against BigQuery data, grant the following roles to the Dataplex Universal Catalog service account:
BigQuery Job User (
roles/bigquery.jobUser) role on the project running the scan; BigQuery Data Viewer (roles/bigquery.dataViewer) role on the tables being scanned. -
To run data profile scans for BigQuery external tables that use Cloud Storage data:
grant the Dataplex Universal Catalog service account the Storage Object Viewer (
roles/storage.objectViewer) and Storage Legacy Bucket Reader (roles/storage.legacyBucketReader) roles on the Cloud Storage bucket. -
To view data profile scan results, jobs, and history:
Dataplex DataScan Viewer (
roles/dataplex.dataScanViewer) role on the project containing the data scan. -
To export data profile scan results to a BigQuery table:
BigQuery Data Editor (
roles/bigquery.dataEditor) role on the table. -
To publish data profile scan results to Dataplex Universal Catalog:
Dataplex Catalog Editor (
roles/dataplex.catalogEditor) role on the@bigqueryentry group. -
To view published data profile scan results in BigQuery on the Data profile tab:
BigQuery Data Viewer (
roles/bigquery.dataViewer) role on the table.
For more information about granting roles, see Manage access to projects, folders, and organizations.
You might also be able to get the required permissions through custom roles or other predefined roles.
Required permissions
If you use custom roles, you need to grant the following IAM permissions:
- To create, run, update, and delete data profile scans:
dataplex.datascans.createon project—Create aDataScandataplex.datascans.updateon data scan—Update the description of aDataScandataplex.datascans.deleteon data scan—Delete aDataScandataplex.datascans.runon data scan—Run aDataScandataplex.datascans.geton data scan—ViewDataScandetails excluding resultsdataplex.datascans.liston project—ListDataScansdataplex.dataScanJobs.geton data scan job—Read DataScan job resourcesdataplex.dataScanJobs.liston data scan—List DataScan job resources in a project
- To allow Dataplex Universal Catalog to run data profile scans against BigQuery data:
bigquery.jobs.createon project—Run jobsbigquery.tables.geton table—Get table metadatabigquery.tables.getDataon table—Get table data
- To run data profile scans for BigQuery external tables that use Cloud Storage data:
storage.buckets.geton bucket—Read bucket metadatastorage.objects.geton object—Read object data
- To view data profile scan results, jobs, and history:
dataplex.datascans.getDataon data scan—ViewDataScandetails including resultsdataplex.datascans.liston project—ListDataScansdataplex.dataScanJobs.geton data scan job—Read DataScan job resourcesdataplex.dataScanJobs.liston data scan—List DataScan job resources in a project
- To export data profile scan results to a BigQuery table:
bigquery.tables.createon dataset—Create tablesbigquery.tables.updateDataon table—Write data to tables
- To publish data profile scan results to Dataplex Universal Catalog:
dataplex.entryGroups.useDataProfileAspecton entry group—Allows Dataplex Universal Catalog data profile scans to save their results to Dataplex Universal Catalog- Additionally, you need one of the following permissions:
bigquery.tables.updateon table—Update table metadatadataplex.entries.updateon entry—Update entries
- To view published data profile results for a table in BigQuery or Dataplex Universal Catalog:
bigquery.tables.geton table—Get table metadatabigquery.tables.getDataon table—Get table data
If a table uses BigQuery row-level
security, then Dataplex Universal Catalog
can only scan rows visible to the Dataplex Universal Catalog service account. To
allow Dataplex Universal Catalog to scan all rows, add its service account to a row
filter where the predicate is TRUE.
If a table uses BigQuery column-level security, then Dataplex Universal Catalog
requires access to scan protected columns. To grant access, give the
Dataplex Universal Catalog service account the
Data Catalog Fine-Grained Reader (roles/datacatalog.fineGrainedReader)
role on all policy tags used in the table. The user creating or updating a data
scan also needs permissions on protected columns.
Grant roles to the Dataplex Universal Catalog service account
To run data profile scans, Dataplex Universal Catalog uses a service account that requires permissions to run BigQuery jobs and read BigQuery table data. To grant the required roles, follow these steps:
Get the Dataplex Universal Catalog service account email address. If you haven't created a data profile or data quality scan in this project before, run the following
gcloudcommand to generate the service identity:gcloud beta services identity create --service=dataplex.googleapis.comThe command returns the service account email, which has the following format:
service-PROJECT_NUMBER@gcp-sa-dataplex.iam.gserviceaccount.com.If the service account already exists, you can find its email by viewing principals with the Dataplex name on the IAM page in the Google Cloud console.
Grant the service account the BigQuery Job User (
roles/bigquery.jobUser) role on your project. This role lets the service account run BigQuery jobs for the scan.gcloud projects add-iam-policy-binding PROJECT_ID \ --member="serviceAccount:service-PROJECT_NUMBER@gcp-sa-dataplex.iam.gserviceaccount.com" \ --role="roles/bigquery.jobUser"Replace the following:
PROJECT_ID: your Google Cloud project ID.service-PROJECT_NUMBER@gcp-sa-dataplex.iam.gserviceaccount.com: the email of the Dataplex Universal Catalog service account.
Grant the service account the BigQuery Data Viewer (
roles/bigquery.dataViewer) role for each table that you want to profile. This role grants read-only access to the tables.gcloud bigquery tables add-iam-policy-binding DATASET_ID.TABLE_ID \ --member="serviceAccount:service-PROJECT_NUMBER@gcp-sa-dataplex.iam.gserviceaccount.com" \ --role="roles/bigquery.dataViewer"Replace the following:
DATASET_ID: the ID of the dataset containing the table.TABLE_ID: the ID of the table to profile.service-PROJECT_NUMBER@gcp-sa-dataplex.iam.gserviceaccount.com: the email of the Dataplex Universal Catalog service account.Create a data profile scan
Console
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click Create data profile scan.
Optional: Enter a Display name.
Enter an ID. See the Resource naming conventions.
Optional: Enter a Description.
In the Table field, click Browse. Choose the table to scan, and then click Select.
For tables in multi-region datasets, choose a region where to create the data scan.
To browse the tables organized within Dataplex Universal Catalog lakes, click Browse within Dataplex Lakes.
In the Scope field, choose Incremental or Entire data.
- If you choose Incremental data, in the Timestamp column field,
select a column of type
DATEorTIMESTAMPfrom your BigQuery table that increases as new records are added, and that can be used to identify new records. For tables partitioned on a column of typeDATEorTIMESTAMP, we recommend using the partition column as the timestamp field.
- If you choose Incremental data, in the Timestamp column field,
select a column of type
Optional: To filter your data, do any of the following:
To filter by rows, click select the Filter rows checkbox. Enter a valid SQL expression that can be used in a
WHEREclause in GoogleSQL syntax. For example:col1 >= 0.The filter can be a combination of SQL conditions over multiple columns. For example:
col1 >= 0 AND col2 < 10.To filter by columns, select the Filter columns checkbox.
To include columns in the profile scan, in the Include columns field, click Browse. Select the columns to include, and then click Select.
To exclude columns from the profile scan, in the Exclude columns field, click Browse. Select the columns to exclude, and then click Select.
To apply sampling to your data profile scan, in the Sampling size list, select a sampling percentage. Choose a percentage value that ranges between 0.0% and 100.0% with up to 3 decimal digits.
For larger datasets, choose a lower sampling percentage. For example, for a 1 PB table, if you enter a value between 0.1% and 1.0%, the data profile samples between 1-10 TB of data.
There must be at least 100 records in the sampled data to return a result.
For incremental data scans, the data profile scan applies sampling to the latest increment.
Optional: Publish the data profile scan results in the BigQuery and Dataplex Universal Catalog pages in the Google Cloud console for the source table. Select the Publish results to BigQuery and Dataplex Catalog checkbox.
You can view the latest scan results in the Data profile tab in the BigQuery and Dataplex Universal Catalog pages for the source table. To enable users to access the published scan results, see the Grant access to data profile scan results section of this document.
The publishing option might not be available in the following cases:
- You don't have the required permissions on the table.
- Another data quality scan is set to publish results.
In the Schedule section, choose one of the following options:
Repeat: Run the data profile scan on a schedule: hourly, daily, weekly, monthly, or custom. Specify how often the scan should run and at what time. If you choose custom, use cron format to specify the schedule.
On-demand: Run the data profile scan on demand.
Click Continue.
Optional: Export the scan results to a BigQuery standard table. In the Export scan results to BigQuery table section, do the following:
In the Select BigQuery dataset field, click Browse. Select a BigQuery dataset to store the data profile scan results.
In the BigQuery table field, specify the table to store the data profile scan results. If you're using an existing table, make sure that it is compatible with the export table schema. If the specified table doesn't exist, Dataplex Universal Catalog creates it for you.
Optional: Add labels. Labels are key-value pairs that let you group related objects together or with other Google Cloud resources.
To create the scan, click Create.
If you set the schedule to on-demand, you can also run the scan now by clicking Run scan.
gcloud
To create a data profile scan, use the
gcloud dataplex datascans create data-profilecommand.If the source data is organized in a Dataplex Universal Catalog lake, include the
--data-source-entityflag:gcloud dataplex datascans create data-profile DATASCAN \ --location=LOCATION \ --data-source-entity=DATA_SOURCE_ENTITY
If the source data isn't organized in a Dataplex Universal Catalog lake, include the
--data-source-resourceflag:gcloud dataplex datascans create data-profile DATASCAN \ --location=LOCATION \ --data-source-resource=DATA_SOURCE_RESOURCE
Replace the following variables:
DATASCAN: The name of the data profile scan.LOCATION: The Google Cloud region in which to create the data profile scan.DATA_SOURCE_ENTITY: The Dataplex Universal Catalog entity that contains the data for the data profile scan. For example,projects/test-project/locations/test-location/lakes/test-lake/zones/test-zone/entities/test-entity.DATA_SOURCE_RESOURCE: The name of the resource that contains the data for the data profile scan. For example,//bigquery.googleapis.com/projects/test-project/datasets/test-dataset/tables/test-table.
C#
C#
Before trying this sample, follow the C# setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog C# API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Go
Go
Before trying this sample, follow the Go setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Go API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Java
Java
Before trying this sample, follow the Java setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Java API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Python
Python
Before trying this sample, follow the Python setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Python API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Ruby
Ruby
Before trying this sample, follow the Ruby setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Ruby API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
REST
To create a data profile scan, use the
dataScans.createmethod.Create multiple data profile scans
You can configure data profile scans for multiple tables in a BigQuery dataset at the same time by using the Google Cloud console.
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click Create data profile scan.
Select the Multiple data profile scans option.
Enter an ID prefix. Dataplex Universal Catalog automatically generates scan IDs by using the provided prefix and unique suffixes.
Enter a Description for all of the data profile scans.
In the Dataset field, click Browse. Select a dataset to pick tables from. Click Select.
If the dataset is multi-regional, select a Region in which to create the data profile scans.
Configure the common settings for the scans:
In the Scope field, choose Incremental or Entire data.
To apply sampling to the data profile scans, in the Sampling size list, select a sampling percentage.
Choose a percentage value between 0.0% and 100.0% with up to 3 decimal digits.
Optional: Publish the data profile scan results in the BigQuery and Dataplex Universal Catalog pages in the Google Cloud console for the source table. Select the Publish results to BigQuery and Dataplex Catalog checkbox.
You can view the latest scan results in the Data profile tab in the BigQuery and Dataplex Universal Catalog pages for the source table. To enable users to access the published scan results, see the Grant access to data profile scan results section of this document.
In the Schedule section, choose one of the following options:
Repeat: Run the data profile scans on a schedule: hourly, daily, weekly, monthly, or custom. Specify how often the scans should run and at what time. If you choose custom, use cron format to specify the schedule.
On-demand: Run the data profile scans on demand.
Click Continue.
In the Choose tables field, click Browse. Choose one or more tables to scan, and then click Select.
Click Continue.
Optional: Export the scan results to a BigQuery standard table. In the Export scan results to BigQuery table section, do the following:
In the Select BigQuery dataset field, click Browse. Select a BigQuery dataset to store the data profile scan results.
In the BigQuery table field, specify the table to store the data profile scan results. If you're using an existing table, make sure that it is compatible with the export table schema. If the specified table doesn't exist, Dataplex Universal Catalog creates it for you.
Dataplex Universal Catalog uses the same results table for all of the data profile scans.
Optional: Add labels. Labels are key-value pairs that let you group related objects together or with other Google Cloud resources.
To create the scans, click Create.
If you set the schedule to on-demand, you can also run the scans now by clicking Run scan.
Run a data profile scan
Console
-
In the Google Cloud console, on the BigQuery
Metadata curation page, go to the Data profiling & quality tab.
- Click the data profile scan to run.
- Click Run now.
gcloud
To run a data profile scan, use the
gcloud dataplex datascans runcommand:gcloud dataplex datascans run DATASCAN \ --location=LOCATION
Replace the following variables:
DATASCAN: The name of the data profile scan.LOCATION: The Google Cloud region in which the data profile scan was created.
C#
C#
Before trying this sample, follow the C# setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog C# API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Go
Go
Before trying this sample, follow the Go setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Go API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Java
Java
Before trying this sample, follow the Java setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Java API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Python
Python
Before trying this sample, follow the Python setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Python API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Ruby
Ruby
Before trying this sample, follow the Ruby setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Ruby API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
REST
To run a data profile scan, use the
dataScans.runmethod.View data profile scan results
Console
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click the name of a data profile scan.
The Overview section displays information about the most recent jobs, including when the scan was run, the number of table records scanned, and the job status.
The Data profile scan configuration section displays details about the scan.
To see detailed information about a job, such as the scanned table's columns, statistics about the columns that were found in the scan, and the job logs, click the Jobs history tab. Then, click a job ID.
gcloud
To view the results of a data profile scan job, use the
gcloud dataplex datascans jobs describecommand:gcloud dataplex datascans jobs describe JOB \ --location=LOCATION \ --datascan=DATASCAN \ --view=FULL
Replace the following variables:
JOB: The job ID of the data profile scan job.LOCATION: The Google Cloud region in which the data profile scan was created.DATASCAN: The name of the data profile scan the job belongs to.--view=FULL: To see the scan job result, specifyFULL.
C#
C#
Before trying this sample, follow the C# setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog C# API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Go
Go
Before trying this sample, follow the Go setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Go API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Java
Java
Before trying this sample, follow the Java setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Java API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Python
Python
Before trying this sample, follow the Python setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Python API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Ruby
Ruby
Before trying this sample, follow the Ruby setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Ruby API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
REST
To view the results of a data profile scan, use the
dataScans.getmethod.View published results
If the data profile scan results are published to the BigQuery and Dataplex Universal Catalog pages in the Google Cloud console, then you can see the latest scan results on the source table's Data profile tab.
In the Google Cloud console, go to the BigQuery page.
In the left pane, click Explorer:
If you don't see the left pane, click Expand left pane to open the pane.
In the Explorer pane, click Datasets, and then click your dataset.
Click Overview > Tables, and then select the table whose data profile scan results you want to see.
Click the Data profile tab.
The latest published results are displayed.
View the most recent data profile scan job
Console
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click the name of a data profile scan.
Click the Latest job results tab.
The Latest job results tab, when there is at least one successfully completed run, provides information about the most recent job. It lists the scanned table's columns and statistics about the columns that were found in the scan.
gcloud
To view the most recent successful data profile scan, use the
gcloud dataplex datascans describecommand:gcloud dataplex datascans describe DATASCAN \ --location=LOCATION \ --view=FULL
Replace the following variables:
DATASCAN: The name of the data profile scan to view the most recent job for.LOCATION: The Google Cloud region in which the data profile scan was created.--view=FULL: To see the scan job result, specifyFULL.
REST
To view the most recent scan job, use the
dataScans.getmethod.View historical scan results
Dataplex Universal Catalog saves the data profile scan history of the last 300 jobs or for the past year, whichever occurs first.
Console
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click the name of a data profile scan.
Click the Jobs history tab.
The Jobs history tab provides information about past jobs, such as the number of records scanned in each job, the job status, and the time the job was run.
To view detailed information about a job, click any of the jobs in the Job ID column.
gcloud
To view historical data profile scan jobs, use the
gcloud dataplex datascans jobs listcommand:gcloud dataplex datascans jobs list \ --location=LOCATION \ --datascan=DATASCAN
Replace the following variables:
LOCATION: The Google Cloud region in which the data profile scan was created.DATASCAN: The name of the data profile scan to view jobs for.
C#
C#
Before trying this sample, follow the C# setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog C# API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Go
Go
Before trying this sample, follow the Go setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Go API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Java
Java
Before trying this sample, follow the Java setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Java API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Python
Python
Before trying this sample, follow the Python setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Python API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Ruby
Ruby
Before trying this sample, follow the Ruby setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Ruby API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
REST
To view historical data profile scan jobs, use the
dataScans.jobs.listmethod.View the data profile scans for a table
To view the data profile scans that apply to a specific table, do the following:
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Filter the list by table name and scan type.
Grant access to data profile scan results
To enable the users in your organization to view the scan results, do the following:
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click the data quality scan you want to share the results of.
Click the Permissions tab.
Do the following:
- To grant access to a principal, click Grant access. Grant the Dataplex DataScan DataViewer role to the associated principal.
- To remove access from a principal, select the principal that you want to remove the Dataplex DataScan DataViewer role from. Click Remove access, and then confirm when prompted.
Manage data profile scans for a specific table
The steps in this document show how to manage data profile scans across your project by using the BigQuery Metadata curation > Data profiling & quality page in the Google Cloud console.
You can also create and manage data profile scans when working with a specific table. In the Google Cloud console, on the BigQuery page for the table, use the Data profile tab. Do the following:
In the Google Cloud console, go to the BigQuery page.
In the Explorer pane (in the left pane), click Datasets, and then click your dataset. Now click Overview > Tables, and select the table whose data profile scan results you want to see.
Click the Data profile tab.
Depending on whether the table has a data profile scan whose results are published, you can work with the table's data profile scans in the following ways:
Data profile scan results are published: the latest published scan results are displayed on the page.
To manage the data profile scans for this table, click Data profile scan, and then select from the following options:
Create new scan: create a new data profile scan. For more information, see the Create a data profile scan section of this document. When you create a scan from a table's details page, the table is preselected.
Run now: run the scan.
Edit scan configuration: edit settings including the display name, filters, sampling size, and schedule.
Manage scan permissions: control who can access the scan results. For more information, see the Grant access to data profile scan results section of this document.
View historical results: view detailed information about previous data profile scan jobs. For more information, see the View data profile scan results and View historical scan results sections of this document.
View all scans: view a list of data profile scans that apply to this table.
Data profile scan results aren't published: click the menu next to Quick data profile, and then select from the following options:
Customize data profiling: create a new data profile scan. For more information, see the Create a data profile scan section of this document. When you create a scan from a table's details page, the table is preselected.
View previous profiles: view a list of data profile scans that apply to this table.
Update a data profile scan
Console
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click the name of a data profile scan.
Click Edit, and then edit the values.
Click Save.
gcloud
To update a data profile scan, use the
gcloud dataplex datascans update data-profilecommand:gcloud dataplex datascans update data-profile DATASCAN \ --location=LOCATION \ --description=DESCRIPTION
Replace the following variables:
DATASCAN: The name of the data profile scan to update.LOCATION: The Google Cloud region in which the data profile scan was created.DESCRIPTION: The new description for the data profile scan.
C#
C#
Before trying this sample, follow the C# setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog C# API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Go
Go
Before trying this sample, follow the Go setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Go API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Java
Java
Before trying this sample, follow the Java setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Java API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Python
Python
Before trying this sample, follow the Python setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Python API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
Ruby
Ruby
Before trying this sample, follow the Ruby setup instructions in the Dataplex Universal Catalog quickstart using client libraries. For more information, see the Dataplex Universal Catalog Ruby API reference documentation.
To authenticate to Dataplex Universal Catalog, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
REST
To edit a data profile scan, use the
dataScans.patchmethod.Delete a data profile scan
Console
In the Google Cloud console, on the BigQuery Metadata curation page, go to the Data profiling & quality tab.
Click the scan you want to delete.
Click Delete, and then confirm when prompted.
gcloud
To delete a data profile scan, use the
gcloud dataplex datascans deletecommand:gcloud dataplex datascans delete DATASCAN \ --location=LOCATION --async
Replace the following variables:
DATASCAN: The name of the data profile scan to delete.LOCATION: The Google Cloud region in which the data profile scan was created.
REST
To delete a data profile scan, use the
dataScans.deletemethod.What's next
- Learn how to explore your data by generating data insights.
- Learn more about data governance in BigQuery.
- Learn how to scan your data for data quality issues.
- Learn how to examine table data and create queries with table explorer.