wx-conrefs.yml

# Do NOT edit this file, to edit conrefs edit the common/conrefs.yml file

attributedefs: >
  {:codeblock: .codeblock}

  {:custom_width: width="550"}

  {:iih: height="20" style="vertical-align:text-bottom"}

  {:biw: style="max-width:90%;height:auto;width:auto"}

  {:external: target="_blank" .external}

  {:java: #java .ph data-hd-programlang='java'}

  {:javascript: #javascript .ph data-hd-programlang='javascript'}

  {:new_window: target="_blank" rel="noopener noreferrer" title="Opens a new
  window or tab"}

  {:php: #php .ph data-hd-programlang='php'}

  {:pre: .pre}

  {:python: #python .ph data-hd-programlang='python'}

  {:r: #r .ph data-hd-programlang='r'}

  {:ruby: #ruby .ph data-hd-programlang='ruby'}

  {:scala: #scala .ph data-hd-programlang='scala'}

  {:screen: .screen}

  {:shortdesc: .shortdesc}

  {:tip: .tip}

  {:important: .important}

  <style>.midd::after { content:"\A\00A0\00A0"; white-space: pre }</style>
kyle: kylewx
AI_Factsheets: AI Factsheets
Amazon_DynamoDB: Amazon DynamoDB
Amazon_EMR_short: Amazon EMR
Amazon_EMR_full: Amazon Elastic Map Reduce
Amazon_S3_short: Amazon S3
Amazon_S3_full: Amazon Simple Storage Service
Amazon_sagemaker: Amazon SageMaker
apis: Watson Data API
aws_glue: AWS Glue
aws_glue_cat: AWS Glue Data Catalog
hbase: Apache HBase
at_full_notm: IBM Cloud Activity Tracker with LogDNA
avatar: Avatar
aws: AWS
aws_long: Amazon Web Services
Anaconda: Anaconda Repository for IBM Cloud Pak for Data
autoai: AutoAI
azure: Microsoft Azure
mssqlserver: Microsoft SQL Server
azure-sql: Microsoft Azure SQL Database
azure-synapse: Microsoft Azure Synapse Analytics
apachehdfs: Apache HDFS
azureblob: Azure Blob Storage
cosmosdb: Azure Cosmos DB
azurefs: Azure File Storage
conn-sdk: IBM Connector SDK
azuredls: Azure Data Lake Storage
hadoopst: Analytics for Apache Hadoop
BigInsightsHDFS: Analytics Engine HDFS
Bluemix: IBM Cloud
Bluemix_short: IBM Cloud
Bluemix_notm: IBM Cloud
redshift: Amazon Redshift
azrds-mysql: Amazon RDS for MySQL
azrds-oracle: Amazon RDS for Oracle
azrds-postresql: Amazon RDS for PostgreSQL
cassandra: Apache Cassandra
cass-opt: Apache Cassandra for DataStage
derby: Apache Derby
hive: Apache Hive
kudu: Apache Kudu
box: Box
cloudera: Apache Impala
cognos: Cognos Analytics
cos_short: Cloud Object Storage
cos: IBM Cloud Object Storage
cos_infra: Cloud Object Storage (infrastructure)
cos_s3: Cloud Object Storage (S3 API)
cp: IBM Cloud Private
cp_short: Cloud Private
cloudant: Cloudant
cpddocs: https://www.ibm.com/docs/SSQNUZ_5.0.x
dynamdashbemb_short: Cognos Dashboard Embedded
composeForMySQL: IBM Cloud Databases for MySQL
composeForPostgreSQL: IBM Cloud Databases for PostgreSQL
dbdatastax: IBM Cloud Databases for DataStax
datastax-op: DataStax Enterprise
databricks: Databricks
databricks-m: Databricks (Manta)
databricks-azure: Microsoft Azure Databricks
dashboards: Cognos Dashboards
ibmdashboards: IBM Dashboards
dashdbshort: dashDB
dashdb_long: IBM dashDB (now named IBM Db2 Warehouse on Cloud)
dashdb_long_bold: '**IBM dashDB** (now named IBM Db2 Warehouse on Cloud)'
data: Cloud Pak for Data
datalong: IBM Cloud Pak for Data
databand: IBM Databand
cpdaas: IBM watsonx
cpdaas_p: Cloud Pak for Data as a Service
installer-full: IBM Cloud Pak for Data control plane
datahub: IBM Knowledge Catalog
datahub_full: IBM Knowledge Catalog
dpx: Data Product Hub
dpx_long: IBM Data Product Hub as a Service
dpx_long_onprem: IBM Data Product Hub
dpriv: Masking flow
drpiv_lc: masking flow
catalog: catalog
classifier_short: Watson Natural Language Classifier
classifier_long: IBM Watson Natural Language Classifier
classifier: Natural Language Classifier
ccs_lower: common core services
ccs_upper: Common Core Services
conversationshort: Watson Assistant
conversationfull: IBM Watson Assistant
cos_swift: Object Storage OpenStack Swift
cos_swift_infra: Object Storage OpenStack Swift (infrastructure)
data_refinery: Data Refinery
data_connect: Data Refinery
data_connect_full: Data Refinery
data_rep: Data Replication
data_rep_full: IBM Data Replication
datastage: DataStage
data_virt: Watson Query
data_virt_cpd: Data Virtualization
data_virt_ui: Data virtualization
data_virt_conn: Data Virtualization
datavirt-full: IBM Watson Query
datavirt-z: Data Virtualization Manager for z/OS
discovery_short: Watson Discovery
discovery_long: IBM Watson Discovery
discovery: Discovery
DSX_short: Watson Studio
DSX_full: IBM Watson Studio
DSX_cloud_full: IBM Watson Studio Cloud
DSX: Watson Studio
DSX_ep: Watson Studio Enterprise
DSX_local: Watson Studio Local
Db2: Db2
db2-dstage: IBM Db2 for DataStage
Db2fori: Db2 for i
Db2forzOS: Db2 for z/OS
Db2forzOS_long: IBM Db2 for z/OS
Db2_Hosted_short: Db2 Hosted
Db2_Hosted_long: IBM Db2 Hosted (previously named IBM DB2 on Cloud)
Db2_on_Cloud_short: Db2 on Cloud
Db2_on_Cloud_long: IBM&reg; Db2 on Cloud
Db2_on_Cloud_long_notm: IBM Db2 on Cloud
Db2Warehouse: Db2 Warehouse
Db2WarehouseonCloud_short: Db2 Warehouse on Cloud
Db2WarehouseonCloud_med: IBM Db2 Warehouse on Cloud
Db2WarehouseonCloud_long: IBM Db2 Warehouse on Cloud (previously named IBM dashDB)
do: Decision Optimization
dq-rules: Data quality rules
eventstore: Db2 Event Store
docker: Docker
dremio: Dremio
dropbox: Dropbox
edb: Databases for EDB
es: Elasticsearch
elastic-cloud: Elastic Cloud
eefah: Execution Engine for Apache Hadoop
exasol: Exasol
flight_service: Flight service
fm_prompt: Prompt Lab
fm_tuning: Tuning Studio
gallery: Resource hub
asset_sample: Resource hub sample
globalrep: global search repository
gbq: Google BigQuery
google-pub-sub: Google Cloud Pub/Sub
governance-console: Governance console
governance-console-long: Governance console on IBM watsonx
gcs: Google Cloud Storage
hadoop-hdfs: HDFS via Execution Engine for Hadoop
hadoop-hive: Hive via Execution Engine for Hadoop
helm: Helm
ikcpremium: IBM Knowledge Catalog Premium
ikcpremiumfull: IBM Knowledge Catalog Premium Cartridge
ikcstandard: IBM Knowledge Catalog Standard
ikcstandardfull: IBM Knowledge Catalog Standard Cartridge
ikcanyedition: IBM Knowledge Catalog any edition
guard-short: Guardium Data Protection
guard-long: IBM Security Guardium Data Protection
iae_short: Analytics Engine
iae_full: IBM Analytics Engine
iae_full_notm: IBM Analytics Engine
iae_cpd_short: Analytics Engine powered by Apache Spark
iae_cpd_full: IBM Analytics Engine powered by Apache Spark
iae_cpd_full_notm: IBM Analytics Engine powered by Apache Spark
iamshort: Cloud Identity and Access Management
IBM: IBM
ibmid: IBMid
IBM_notm: IBM
icp: IBM Cloud Pak
ifpc: Informatica PowerCenter
igc_short: Information Governance Catalog
igc_long: IBM InfoSphere Information Governance Catalog
ieeh: Impala via Execution Engine for Hadoop
impala: Impala
Informix: Informix
iis: InfoSphere Information Server
kafka: Apache Kafka
kafka-short: Kafka
k_studio_short: Watson Knowledge Studio
k_studio_long: IBM Knowledge Studio
k_studio: Knowledge Studio
keymanagementservicefull: IBM Key Protect for IBM Cloud
keymanagementserviceshort: Key Protect
looker: Google Looker
mariadb: MariaDB
mdm-oc_full: IBM Match 360 with Watson
mdm-oc_short: IBM Match 360
m3: Match 360
ipm-full: IBM Product Master
ipm-short: Product Master
message_hub: Event Streams
message_hub_full: IBM Event Streams
meta-enrich: Metadata enrichment
meta-import: Metadata import
meta-import-discovery: Metadata import (discovery)
meta-import-lineage: Metadata import (lineage)
microstrategy: MicroStrategy
milvus: Milvus
minio: MinIO
mongo: MongoDB
mongodb: IBM Cloud Databases for MongoDB
mq: MQ
mq-long: IBM MQ
mysql: MySQL
nlc_full: IBM Watson Natural Language Classifier
nlc: Natural Language Classifier
nlp: Watson Natural Language Processing
nlpfull: IBM Watson Natural Language Processing
nlufull: IBM Watson Natural Language Understanding
nlushort: Natural Language Understanding
odata: OData
odi: Open Data for Industries
openlineage: OpenLineage
oracle: Oracle
oracle-dstage: Oracle Database for DataStage
oraclebi: Oracle Business Intelligence Enterprise Edition
oracledi: Oracle Data Integrator
p_insights_short: Watson Personality Insights
p_insights_long: IBM Watson Personality Insights
p_insights: Personality Insights
pipeline_full: IBM Orchestration Pipelines
pipeline_short: Orchestration Pipelines
pipeline: Pipelines
pivgreenplum: Greenplum
pc: Connectivity
pconn: Platform assets
pm_short: Machine Learning
pm_wml: Watson Machine Learning
pm_full: IBM Watson Machine Learning
plananalytics: Planning Analytics
postgresql: PostgreSQL
powerbi: Power BI
powerbi-desktop: Microsoft Power BI Desktop
powerbi-rs: Microsoft Power BI (Azure)
PureData: Netezza Performance Server
nzopt: IBM Netezza Performance Server for DataStage
qlik: Qlik Sense
rhos-short: OpenShift
rhos-long: Red Hat OpenShift
sapase: SAP ASE
sapbo: SAP BusinessObjects
sapbapi: SAP BAPI
sapiq: SAP IQ
sapodata: SAP OData
saphana: SAP HANA
sapbulk: SAP Bulk Extract
sapdelta: SAP Delta Extract
sapidoc: SAP IDoc
sapabap: SAP Data Dictionary
sap-s4hana: SAP S/4HANA
sas: Statistical Analysis System
sat_long: IBM Cloud Satellite
sat: Satellite
satlink: Satellite Link
satloc: Satellite location
satctr: Satellite Connector
singlestore: SingleStoreDB
spark_short: Apache Spark
spark_long: IBM Apache Spark
spark: Spark
speechtext_short: Watson Speech to Text
speechtext_full: IBM Watson Speech to Text
speechtext: Speech to Text
snowflake: Snowflake
spssas: SPSS Analytic Server
spss_modeler: SPSS Modeler
sqldb: SQL Database
sqlquery: IBM Cloud Data Engine
sqlquery-short: Cloud Data Engine
ssas: Microsoft SQL Server Analysis Services
ssis: Microsoft SQL Server Integration Services
ssrs: Microsoft SQL Server Reporting Services
st-volume: Storage volume
streaminganalyticsshort: Streaming Analytics
streaminganalyticslong: IBM Streaming Analytics
streams_short: Streams Designer
streams_long: IBM Streams Designer
svsdio_long: IBM Streams Flows Extension for Microsoft Visual Studio Code
svsdio: Streams Flows extension for VS Code
synthetic: Synthetic Data Generator
tableau: Tableau
talend: Talend
tera: Teradata
tera-dstage: Teradata database for DataStage
textspeech_short: Watson Text to Speech
textspeech_full: IBM Watson Text to Speech
textspeech: Text to Speech
till: Tiller
tone_short: Watson Tone Analyzer
tone_long: IBM Watson Tone Analyzer
tone: Tone Analyzer
translator_short: Watson Language Translator
translator_long: IBM Watson Language Translator
translator: Language Translator
vertica: Vertica
visu: Visualizations
Visutab: Visualization
WA_short: Watson Analytics
WA_long: IBM Watson Analytics
wx-platform: watsonx
wx-platform_cap: Watsonx
wx-platform_full: IBM watsonx as a Service
wxai: watsonx.ai
wxai_cap: Watsonx.ai
wxai_full: IBM watsonx.ai
wxai_lite: watsonx.ai lightweight engine
wxdata_full: IBM watsonx.data
wxdata_cap: Watsonx.data
wxdata: watsonx.data
watsonxd-conn: watsonx.data Presto
wxgov: watsonx.governance
wxgovernance_cap: Watsonx.governance
wxgovernance_full: IBM watsonx.governance
wmla: Watson Machine Learning Accelerator
wmla_full: IBM Watson Machine Learning Accelerator
Platform: IBM Watson
Platform_full: IBM Watson
presto: Presto
visualrecognitionfulltm: IBM Watson Visual Recognition
visualrecognitionfull: IBM Watson Visual Recognition
visualrecognitionshort: Visual Recognition
ais_full: IBM Watson OpenScale
ais_short: Watson OpenScale
ais: Watson OpenScale
wos4d_full: IBM Watson OpenScale for IBM Cloud Pak for Data
wos4d_notm: IBM Watson OpenScale for IBM Cloud Pak for Data
op_platform: IBM OpenPages with Watson
op_mrg: IBM OpenPages Model Risk Governance
op_short: IBM OpenPages
op_shorter: OpenPages
ai_func: AI function
ai_func_pl: AI functions
bigsql: Db2 Big SQL
bigsql_full: IBM Db2 Big SQL
objectdetectionfulltm: IBM Watson Object Detection
objectdetectionfull: IBM Watson Object Detection
objectdetectionshort: Object Detection
connectivity: >-
  For **Private connectivity**, to connect to a database that is not
  externalized to the internet (for example, behind a firewall), you must set up
  a [secure connection](securingconn.html).
jdbc-cpd: >-
  See [Importing JDBC drivers](../../cpd/admin/jdbc-drivers.html) for the
  procedure and required permissions to upload the JAR file to Cloud Pak for
  Data. **Important**: By default, uploading JDBC driver files is disabled and
  users cannot view the list of JDBC drivers in the web client. An administrator
  must [enable users to upload or view JDBC
  drivers](../../cpd/admin/post-install-enable-jdbc-upload.html).
chooseproject: >-
  Click **Assets > New asset > Connect to a data source**. See [Adding a
  connection to a project](create-conn.html).
v-cred-ssl: >-
  For **Credentials** and **Certificates**, you can use secrets if a vault is
  configured for the platform and the service supports vaults. For information,
  see [Using secrets from vaults in connections](vaults-conn.html).
v-cred: >-
  For **Credentials**, you can use secrets if a vault is configured for the
  platform and the service supports vaults. For information, see [Using secrets
  from vaults in connections](vaults-conn.html).
v-ssl: >-
  For **Certificates**, you can use secrets if a vault is configured for the
  platform and the service supports vaults. For information, see [Using secrets
  from vaults in connections](vaults-conn.html).
choosecatalog: >-
  Click **Add to catalog > Connection**. See [Adding a connection asset to a
  catalog](../catalog/c-add-conn.html).
choosedsp: >-
  Click **Import assets > Data access > Connection**. See [Adding data assets to
  a deployment space](../analyze-data/ml-space-add-assets.html).
dataproject: See [Add data from a connection in a project](connected-data.html).
datacatalog: See [Add data from a connection in a catalog](../catalog/conn-data.html).
experimental: >-
  <span class="carbon-tag-magenta bx--tag bx--tag--magenta">Experimental</span>
  This is an experimental release and is not yet supported for use in production
  environments.
dpxcreds: >-
  Data Product Hub uses the credentials of the connection owner to create and
  deliver data products. The personal credentials entered by the connection
  owner are automatically saved and used to create and deliver data products.
dph-conn: >-
  **Data Product Hub**

  :   You can connect to this data source from Data Product Hub. For
  instructions, see [Connectors for Data Product
  Hub](../../wsj/data-products/dph_conn_types.html).
pv: Version 1.1
pv2: Version 2.0.0-1
number2: 2\.0\.0-1
watson: Watson
wml: Watson Machine Learning
wmls: Watson Machine Learning Server
wmls-full: IBM Watson Machine Learning Server
service-label: <span class="carbon-tag-blue bx--tag bx--tag--blue">Service</span>
tech-preview: >-
  <span class="carbon-tag-magenta bx--tag bx--tag--magenta">Tech preview</span>
  This is a technology preview and is not yet supported for use in production
  environments.
lineage: lineage
Lineage: Lineage
preinstall-elasticsearch: >
  Log in as a system administrator and set the virtual memory kernel parameter
  to `262144` on every compute node in the cluster to support the Elasicsearch
  microservice. Elasticsearch helps in checking the health of your clusters and
  creating data visualizations.


  Set the parameter on every node in the cluster:

  ```

  echo "vm.max_map_count=262144" >> /etc/sysctl.conf ; sysctl -p

  ```

  If you don't set the parameter, the Elasticsearch pod fails with the following
  error message:

  ```

  ERROR: [1] bootstrap checks failed

  [1]: max virtual memory areas vm.max_map_count [65530] is too low, increase to
  at least [262144]

  ```
timezone-master-node: >
  If the service will be installed on a remote machine that runs in a different
  time zone than the master node, the time zone for the master node is
  overwritten by the time zone for the installer node. This time zone
  discrepancy results in scheduled jobs that don't run at the correct time.


  If necessary, log in as a system administrator and set the timezone for the
  master node:

  1. Locate the [tz database code
  format](https://access.redhat.com/documentation/en-us/red_hat_virtualization/4.0/html-single/version_3_rest_api_guide/index#appe-Timezones)
  associated with the master node time zone.

  1. If the `override.yaml` file does not exist, create it.

  1. Add the tz database code value to the `override.yaml` file. For example, if
  you're using the America/Los_Angeles database code, add the following value:
      ```
      global:
         masterTimezone: 'America/Los_Angeles'
      ```
  1. Inform the user who is installing the service to include the `--override
  override.yaml` option in the installation command.
salesforce: |
  Salesforce
sfc: Salesforce.com
salesforce-opt: Salesforce API for DataStage
services-install_role: >
  **Required role:** To complete this task, you must be an administrator of the
  project (namespace) where you will deploy the service.
services-install_prereq: >
  **Prerequisite:** Watson Studio Local must be installed on your cluster before
  you can install this service. See [Installing Watson Studio
  Local](../install/install-ws.html).
services-install_1: >
  1. Transfer the service tar file to the cluster.

  1. Extract the service tar file in the same directory where the Watson Studio
  Local tar file was extracted.
services-install_2: |
  1. Push the Docker images to the registry by running this command:
services-install_3: |
  1. Install the setup administration and security by running this command:
services-install_4: |
  1. Install the service by running this command:
services-install_icparg: >
  Include the `--icp` argument if you are installing the service on an IBM Cloud
  Private cluster.
services-install_override: >
  Include the `--override override.yml` argument if the cluster administrator
  set the time zone for the master node
services-install-vars: >
  Ensure that you have information from your cluster administrator so that you
  can replace the following values in the installation commands:


  - `<Package_location>` → The installation directory where the Watson Studio
  Local tar file was extracted.

  - `<Registry_password>` → The password for the Docker registry.

  - `<Registry_username>` → The user name for the Docker registry.

  - `<Assembly_version>` → The version of the service assembly to install.

  - `<Storage_class_name>` → The name of the storage class to use to provision
  storage for the service.

  - `<Registry_location>` → The location to store the images in the registry
  server.

  - `<Registry_from_cluster>` → The location from which pods on the cluster can
  pull images.

  - `<Project>` → The project (namespace) where the Watson Studio Local control
  plane is installed.

  - `<Install_override_file>` → The name of the `override.yaml` file.
config-custom-certs: >
  You can use your existing certificates and not have to modify the system
  truststore. The following configuration properties convert DSXHI to do the
  following customizations:


  **custom_jks**

  :   DSXHI typically generates a Keystore, converts it to a `.crt`, and adds
  the `.crt` to the Java Truststore. However, with this configuration, DSXHI
  allows you to provide a custom Keystore that can be used to generate the
  required `.crt`.


  **dsxhi_cacert**

  :   DSXHI previously detected the appropriate truststore to use as part of the
  installation. With the `dsxhi_cacert` property, DSXHI allows you to provide
  any custom truststore (CACERTS), where DSXHI certs are added.


  **add_certs_to_truststore**

  :   This configuration provides options to either add the host certificate to
  the truststore yourself or DSXHI adds it. If you set the configuration to
  False, users must add the host certificate to the truststore themselves. DSXHI
  doesn't make any changes to the truststore. If you set the configuration to
  True, DSXHI retains its default behavior to add host certificate to java
  truststore and on detected datanodes for gateway and web services.
action: >-
  <button class="bx--tag bx--tag--red"><span class="bx--tag__label">Action
  required</span></button>
cloud-new-plan: >-
  <button class="bx--tag bx--tag--teal"><span
  class="bx--tag__label">New</span></button> This information describes the new
  service plan.
startofchange: >-
  <button class="bx--tag bx--tag--magenta"><span class="bx--tag__label">Start of
  change</span></button>
endofchange: >-
  <button class="bx--tag bx--tag--magenta"><span class="bx--tag__label">End of
  change</span></button>
question: >-
  <button class="bx--tag bx--tag--red"><span
  class="bx--tag__label">Question</span></button>
beginner: >-
  <button class="bx--tag bx--tag--green"><span
  class="bx--tag__label">Beginner</span></button>
intermediate: >-
  <button class="bx--tag bx--tag--blue"><span
  class="bx--tag__label">Intermediate</span></button>
advanced: >-
  <button class="bx--tag bx--tag--purple"><span
  class="bx--tag__label">Advanced</span></button>
nocode: >-
  <button class="bx--tag bx--tag--green"><span class="bx--tag__label">No
  code</span></button>
lowcode: >-
  <button class="bx--tag bx--tag--blue"><span class="bx--tag__label">Low
  code</span></button>
allcode: >-
  <button class="bx--tag bx--tag--purple"><span class="bx--tag__label">All
  code</span></button>
cont: >-
  <button class="bx--tag bx--tag--red"><span
  class="bx--tag__label">Continuation</span></button>
df_data: Data integration
df_AI: AI governance
df_pipeline: Orchestrate an AI pipeline
df_data_science: Data Science and MLOps
df_pipeline_tut1: Orchestrate an AI pipeline with data integration
df_pipeline_tut2: Orchestrate an AI pipeline with model monitoring
df_360: Master Data Management
df_govern: Data governance
create_connection: New asset > Connect to a data source
create_synthetic_data: New asset > Generate synthetic tabular data
create_prompt: New asset > Chat and build prompts with foundation models
create_tuning: New asset > Tune a foundation model with labeled data
create_vector_index: New asset > Ground gen AI with vectorized documents
create_dr: New asset > Prepare and visualize data
create_autoai: New asset > Build machine learning models automatically
create_spss: New asset > Build models as a visual flow
create_do: New asset > Solve optimization problems
create_fl: New asset > Train models on distributed data
create_notebook: New asset > Work with data and models in Python or R notebooks
create_pipeline: New asset > Automate model lifecycle
create_masking: New asset > Copy and mask data
create_metadata_enr: New asset > Enrich data assets with metadata
create_metadata_imp: New asset > Import metadata for data assets
create_query: New asset > Create a dynamic view of data
create_replicate: New asset > Replicate data
create_ds: New asset > Transform and integrate data
create_ds_component: New asset > Create reusable DataStage components
create_data_quality_definition: New asset > Define how to measure data quality
create_data_quality_rule: New asset > Measure and monitor data quality
create_parameter_set: New asset > Define resuable sets of parameters
create_dashboard: New asset > Visualize data in dashboards
create_experiment: New Asset > Build deep learning experiments
create_mdm_configuration: New Asset > Consolidate data into 360-degree views
predefined_terms: >-
  Predefined business terms and the Knowledge Accelerator Sample Personal Data
  category that includes them are available only if you create a Watson
  Knowledge Catalog service instance with a Lite or Standard plan after 7
  October 2022. For more information see [Predefined business
  terms](predefined-business-terms.html).
data_lineage: IBM Manta Data Lineage
data_lineage_short: Manta Data Lineage
manta: MANTA Automated Data Lineage for IBM Cloud Pak for Data
manta_short: MANTA Automated Data Lineage
manta_alone: MANTA
manta_admin_ui: Automatic Data Lineage
manta_install_guide: >-
  MANTA Automated Data Lineage for IBM Cloud Pak for Data Installation and Usage
  Manual
manta_use_guide: >-
  MANTA Automated Data Lineage for IBM Cloud Pak for Data Visualization User
  Documentation
manta_admin_guide: MANTA Automated Data Lineage for IBM Cloud Pak for Data Server Administration
manta_architecture_guide: >-
  MANTA Automated Data Lineage for IBM Cloud Pak for Data Container Architecture
  (36.x)
manta_openshift_guide: >-
  Guide to Managing MANTA Automated Data Lineage on IBM Cloud Pak for Data on
  OpenShift Using Operator (36.x)
manta_docset_URL: https://www.ibm.com/support/pages/node/6597457
svc-install: >-
  <span class="carbon-tag-blue bx--tag bx--tag--blue">Service</span> This
  service is not available by default. An administrator must install this
  service on the IBM Cloud Pak for Data platform, and you must be given access
  to the service. To determine whether the service is installed, open the
  Services catalog and check whether the service is enabled.
icpd-optional: >-
  <button class="bx--tag bx--tag--blue"><span
  class="bx--tag__label">Optional</span></button> This feature is not available
  by default.
unreal_data: Unreal Data