SSIJV2 - Documentation Index
Table of Contents
Welcome
Documentation home
Overview of the Data Fabric experience
What's new
Use cases
Data fabric use case
Data integration use case
Feature differences between Data Fabric experience deployments
Feature differences between watsonx.data intelligence deployments
Feature differences between watsonx.data integration deployments
Feature differences between watsonx.data integration and separate service offerings
Platform architecture
Asset types and properties
Previews
Profiles
Data quality
Relationships
Visualizations
Activities
Searching for assets and artifacts
Object storage for workspaces
AI agents and augmentations
AI augmentations in curation tools
Services
Regional availability
watsonx.data intelligence plans
IBM Cloud feature differences between plans
AWS feature differences between plans
watsonx.data integration plans
IBM Cloud services
Creating and managing services
IBM Cloud Object Storage plans
AWS services
AWS GovCloud services
Known issues and limitations
FAQ
Browser support
Language support
Preview releases
Notices
Accessibility
Get help
Getting started and tutorials
Signing up for the Data Fabric experience
Getting started with watsonx.data intelligence
Getting started with data governance and catalog
Getting started with data quality
Getting started with data lineage
Getting started with Data Product Hub
Getting started with Data Intelligence Agent
Getting started with watsonx.data intelligence MCP server
Installing the local MCP server
MCP configuration file and environment variables
Configuring IBM Bob
Configuring Claude Desktop
Configuring watsonx Orchestrate
Configuring GitHub Copilot in Visual Studio Code
Setting up and using skills
Inviting users
Getting started with watsonx.data integration
Switching between experiences
Creating task credentials
Generating an API key and bearer token
watsonx APIs and SDKs
Tutorials
Curate high quality data
Protect your data
Consume your data
Replicate data
Stream data
Transform batch data
Observe data
Projects
Shared projects across experiences
Creating a project
Importing a project
Importing project assets
Administering projects
Managing collaborators
Project collaborator roles
Marking a project as sensitive
Managing task credentials
Adding associated services
Exporting project assets
Enabling folders
Switching the experience for a project
Defining default settings for tools
Data intelligence
Providing additional context for SQL generation
Data quality
Job execution windows
Metadata enrichment
CSV file for rule-based term assignment
Tuning term assignment
Custom abbreviation files for name generation
Unstructured Data Integration
Managing assets in projects
Organizing assets with folders
Downloading data assets
Choosing compute resources for tools
Compute options for Data Refinery
Compute options for DataStage
Compute options for Pipelines
Managing compute resources
Creating non-standard environment templates
Customizing environment templates
Examples of customizations (before 25.1)
Examples of customizations (from 25.1)
Runtime usage
Creating and managing jobs
Creating jobs in Data Refinery
Creating jobs in DataStage
Creating jobs for running data quality rules
Creating jobs for Pipelines
Viewing jobs across projects
Adding catalog assets to a project
Publishing assets to a catalog
Leaving a project
Markdown cheatsheet
Preparing data
Adding data to a project
Adding very large files to a project
Adding connections to projects
Adding integrated service connectors
Connecting to data behind a firewall
Adding data from a connection
Adding a dynamic view of data from a connection
Adding a query-based asset
Providing additional context for text-to-SQL conversions
Adding segmented assets
Adding a connected folder asset from a connection
Connectors
AlloyDB for PostgreSQL
Amazon Aurora for MySQL
Amazon Aurora for PostgreSQL
Amazon DynamoDB
Amazon RDS for MySQL connection
Amazon RDS for Oracle connection
Amazon RDS for PostgreSQL connection
Amazon Redshift connection
Amazon S3 connection
Setting up temporary credentials or a Role ARN for Amazon S3
Apache Cassandra connection
Apache Cassandra for DataStage connection
Apache Derby connection
Apache HDFS connection
Apache Hive connection
Apache Impala connection
Apache Kafka connection
Apache Spark SQL connection
AWS Databricks
Box connection
ClickHouse connection
Collibra connection
Confluence connection
Databricks Delta Lake connection
DataStax Astra connection
DataStax Enterprise connection
DataStax HCD connection
Denodo connection
Dremio connection
Dropbox connection
Elasticsearch connection
Elastic Cloud connection
FTP connection
Generic S3 connection
Google BigQuery connection
Workload identity federation examples
Google Cloud Pub/Sub connection
Google Cloud Storage connection
Google Drive connection
Google Looker connection
Greenplum connection
HTTP connection
IBM Cloud Data Engine connection
IBM Cloud Databases for MongoDB connection
IBM Cloud Databases for MySQL
IBM Cloud Databases for PostgreSQL connection
IBM Cloud Object Storage connection
Controlling access to Cloud Object Storage buckets
IBM Cloud Object Storage (infrastructure) connection
IBM Cloudant connection
IBM Cognos Analytics connection
IBM Data Virtualization connection
IBM Data Virtualization Manager for z/OS connection
IBM DataStage for Cloud Pak for Data connection
IBM Db2 connection
IBM Db2 for DataStage connection
IBM Db2 Big SQL connection
IBM Db2 for i connection
IBM Db2 for z/OS connection
IBM Db2 on Cloud connection
IBM Db2 Warehouse connection
IBM FileNet P8 connection
IBM Informix connection
IBM Master Data Management connection
IBM MQ connection
IBM Netezza Performance Server connection
IBM Netezza Performance Server for DataStage connection
IBM Planning Analytics connection
IBM watsonx.data Milvus connection
IBM watsonx.data Presto connection
IBM watsonx.data SharePoint connection
Iceberg metastore connection
Informatica PowerCenter connection
JDBC connection
JMS connection
MariaDB connection
Microsoft Azure Blob Storage connection
Microsoft Azure Cosmos DB connection
Microsoft Azure Data Lake Storage connection
Microsoft Azure Databricks connection
Microsoft Azure Fabric Warehouse connection
Microsoft Azure File Storage connection
Microsoft Azure PostgreSQL connection
Microsoft Azure SQL Database connection
Microsoft Azure Synapse Analytics connection
Microsoft OneDrive connection
Microsoft Power BI (Azure) connection
Microsoft Power BI (Local) connection
IBM watsonx.data SharePoint connection
Microsoft SharePoint Files connection
Microsoft SharePoint connection
Microsoft SQL Server connection
Microstrategy connection
Milvus connection
MongoDB connection
MySQL connection
OData connection
ODBC connection
OpenLineage connection
OpenSearch connection
OpenSearch IBM Cloud connection
Oracle connection
Oracle Database for DataStage connection
PostgreSQL connection
Presto connection
Salesforce.com connection
Salesforce API for DataStage connection
SAP ASE connection
SAP IQ connection
SAP OData connection
SingleStoreDB connection
Slack connection
Snowflake connection
Splunk connection
Statistical Analysis System (SAS) connection
Tableau connection
Talend Data connection
Teradata connection
Teradata database for DataStage connection
Trino connection
Vertica connection
Web client connection
Adding platform connections
Building custom connectors with Connector forge
Creating and deploying custom connectors
Troubleshooting custom connectors
Parametrized connections
Data protection with data source definitions
Protection solutions for data source definition
Connectors that support data source definitions
Connectors with hard-coded data source identity properties
Roles and asset privacy settings for data source definitions
Creating a data source definition
Creating a data source definition from the Data source definition list
Adding endpoints to a new or existing data source definition
Creating a connection from the Data source definitions list
Setting connection limits for data source definitions
Editing, deactivating, activating, or deleting data source definitions
Managing feature groups (beta)
Orchestrating tasks with Orchestration Pipelines
Getting started with Pipelines
Planning a pipeline
Creating a pipeline
Configuring pipeline nodes
Managing default settings
Configuring global objects
Adding conditions to a pipeline
Functions used in pipelines Expression Builder
DataStage functions used in pipelines Expression Builder
Handling pipeline errors
Programming a pipeline
Creating custom components
Running and saving pipelines
Configuration management for Orchestration Pipelines
Curating and integrating unstructured data
Supported connectors for curation of unstructured data
Setting up curation flows for unstructured data
Designing unstructured data curation flows
Document classes
Schema requirements
Managing document classes
Integrating unstructured data documents
Creating data integration flows
Working with parameters
Running a flow with Spark
Debugging a flow
Data preparation nodes
Ingest data
Extract data
Quality
Transform data
Generate output
Custom nodes
Curating structured data
Supported connectors for discovery, enrichment, and data quality
Supported connectors for lineage import
Amazon RDS for Oracle lineage configuration
Amazon RDS for PostgreSQL lineage configuration
Amazon Redshift lineage configuration
Apache Hive lineage configuration
Google BigQuery lineage configuration
Greenplum lineage configuration
IBM Cloud Databases for PostgreSQL lineage configuration
IBM Cognos Analytics lineage configuration
IBM DataStage for Cloud Pak for Data lineage configuration
IBM Db2 lineage configuration
IBM Db2 for z/OS lineage configuration
IBM Db2 on Cloud lineage configuration
Informatica PowerCenter lineage configuration
Microsoft Azure Databricks lineage configuration
Microsoft Azure SQL Database lineage configuration
Microsoft Power BI (Azure) lineage configuration
Microsoft Power BI Report Server lineage configuration
Microsoft SQL Server lineage configuration
Microsoft SQL Server Integration Services (SSIS) lineage configuration
MicroStrategy lineage configuration
OpenLineage lineage configuration
Oracle lineage configuration
PostgreSQL lineage configuration
Qlik Sense lineage configuration
SAP BusinessObjects lineage configuration
Snowflake lineage configuration
Statistical Analysis System (SAS) lineage configuration
Tableau lineage configuration
Talend lineage configuration
Teradata lineage configuration
YugabyteDB lineage configuration
Importing metadata
Designing metadata imports
Configuring metadata import for data integration assets
Creating metadata imports
Managing existing metadata imports
Metadata import jobs
Enriching your data assets
Designing metadata enrichments
Term assignment
Best practices
Random sampling concepts
Creating an enrichment asset
Managing existing enrichments
Managing enrichment jobs
Monitoring job runs
Reviewing enrichment results
Profile details
Frequency distributions
Reviewing results in a spreadsheet program
Making bulk changes to assignments
Managing data quality checks
Identifying primary keys
Identifying relationships
Advanced data profiling
Publishing enrichment results
Managing data quality
Data quality dimensions
Types of predefined data quality checks
Data quality assets
Managing data quality definitions
Building blocks for rule logic
Sample data quality definitions
Sample rule expressions
Reserved words
Managing data quality rules
Creating rules from data quality definitions
Creating SQL-based rules
Sample SQL rules
Configuring output settings for rules
Assessing data quality with rules
Data quality analysis results
Data quality scores
Data quality SLA compliance and remediation
Ensuring data quality with data contracts
Automating data quality remediation
Refining data
Adding data to Data Refinery
Validating your data
Visualizing your data
Managing Data Refinery flows
Target connection options
GUI operations
Interactive code templates
Supported data sources for Data Refinery
Visualizing your data
Chart types
3D charts
Bar charts
Box plots
Bubble charts
Candlestick charts
Circle packing charts
Custom charts
Dendrogram charts
Dual Y-axes charts
Error bar charts
Evaluation charts
Heat map charts
Histogram charts
Line charts
Map charts
Math curve charts
Multi-chart charts
Multiple series charts
Parallel charts
Pareto charts
Pie charts
Population pyramid charts
Q-Q plots
Radar charts
Relationship charts
Scatter plots and dot plots
Scatter matrix charts
Series array charts
Sunburst charts
t-SNE charts
Time plots
Theme River charts
Tree charts
Treemap charts
Word cloud charts
Global visualization preferences
Data integration
Transforming data with DataStage
Finding resource usage
Designing flows
Asset browser
DataStage stages
Aggregator
Fast path
Stage tab
Calculation and recalculation dependent properties
Bloom Filter
Stage tab
Change Apply
Example data (DataStage)
Fast path
Change Capture
Fast path
Stage tab
Checksum
Adding a Checksum column to your data (DataStage)
Properties for Checksum Stage (DataStage)
Mapping output columns (DataStage)
Specifying execution options (DataStage)
Column Export
Fast path
Stage tab
Input tab
Output tab
Column Generator
Fast path
Stage tab
Column Import
Examples (DataStage)
Fast path
Stage tab
Input tab
Output tab
Combine Records
Examples (DataStage)
Example 1 (DataStage)
Example 2 (DataStage)
Fast path
Stage tab
Properties section
Outputs section
Combine keys section
Options section
Advanced section
NLS Locale section
Compare
Fast path
Stage tab
Compress
Fast path
Stage tab
Copy
Fast path
Stage tab
Decode
Fast path
Difference
Fast path
Stage tab
Distributed Transaction
Encode
Fast path
Stage tab
Excel
Configuring the Excel stage as a source
Configuring the Excel stage as a target
Extracting the data from Microsoft Excel
Examples of extracting data from Microsoft Excel files
Examples of writing data to Microsoft Excel files
Reference
Properties reference: Excel
Data type conversions from Microsoft Excel to IBM DataStage
Data type conversions from DataStage to Microsoft Excel
Job abort conditions in Microsoft Excel
Consideration about end of wave
Expand
Fast path
Stage tab
External Filter
Fast path
Stage tab
External Source
Fast path
Stage tab
Advanced section
NLS Map section
Output tab
Properties section
Source section
Options section
Format section
Using RCP With External Source Stages (DataStage)
External Target
Fast path
Stage tab
Advanced section
NLS Map section
Input tab
Input link properties section
Target section
Options section
Format section
Output tab
Using RCP with External Target stages (DataStage)
Filter
Specifying the filter
Input data columns
Supported Boolean expressions and operators
Order of association (DataStage)
String comparison (DataStage)
Fast path
Stage tab
Funnel
Fast path
Stage tab
Link Ordering section
Generic
Fast path
Stage tab
Head
Fast path
Stage tab
Hierarchical data
Using the Hierarchical Data stage (DataStage)
Adding a Hierarchical Data stage to a (DataStage) flow
Configuring runtime properties for the Hierarchical Data stage (DataStage)
The assembly (DataStage)
Input step (DataStage)
Output step (DataStage)
Assembly Editor (DataStage)
Opening the Assembly Editor (DataStage)
Schema views
Mapping data (DataStage)
Working with the mapping table (DataStage)
Determining mapping candidates (DataStage)
Configuring how mapping candidates are determined (DataStage)
XML Composer step (DataStage)
XML Composer validation rules (DataStage)
XML Parser step (DataStage)
XML Parser validation rules (DataStage)
Setting default values for types (DataStage)
JSON transformation (DataStage)
Schema management (DataStage)
Opening the Schema Library Manager (DataStage)
Working with libraries and resources (DataStage)
Creating a JSON schema in the schema library (DataStage)
JSON Parser step (DataStage)
JSON Parser validation rules (DataStage)
JSON Composer step (DataStage)
JSON Composer validation rules (DataStage)
REST operator in (DataStage)
REST step pages
General
Security
Request
Response
Mappings
Output schema of the REST step
Passing multiple rows from an XML or JSON file
Transformation steps for the Hierarchical Data stage (DataStage)
Aggregate step (DataStage)
H-Pivot step (DataStage)
HJoin step (DataStage)
Order Join step (DataStage)
Regroup step (DataStage)
Sort step (DataStage)
Union step (DataStage)
V-Pivot step (DataStage)
Java Integration
Java code integration
Setting up your development environment
Implementing abstract methods of the Processor class
Compiling the Java code
Running the Java code on the Parallel Engine, Java Integration stage
Accessing Stage Configuration
Declaring the Capabilities of the Java code
Reading Records from Input Link
Writing Records to Output Link
Rejecting Records
Looking up data in the Sparse lookup mode
Data Types
Retrieving Column Metadata on the Link
Using user-defined properties
Runtime column propagation
Running the Java code on the conductor node
Transferring data from the conductor node to player nodes
Logging messages with the Java Integration stage
Terminating a job from the Java code
Using JavaBeans
User Defined Function
Designing jobs with the Java Integration stage
Configuring Java Integration stage as a source
Configuring Java Integration stage as a transformer
Configuring Java Integration stage as a target
Looking up data by using reference links
Setting up column definitions
Java libraries
Properties reference: Java Integration
Join
Join versus lookup
Fast path
Stage tab
Lookup
Lookup versus Join
Fast path
Properties
Stage tab
Input and Output tab
Sparse and normal Lookup
Make Subrecord
Fast path
Stage tab
Examples (DataStage)
Make Vector
Examples (DataStage)
Example 1 (DataStage)
Example 2 (DataStage)
Fast path
Stage tab
Properties section
Options section
Advanced section (DataStage)
Merge
Fast path
Stage tab
Modify
Fast path
Stage tab
Peek
Fast path
Stage tab
Pivot Enterprise
Specifying a horizontal pivot operation (DataStage)
Specifying a horizontal pivot operation and mapping output columns (DataStage)
Example of horizontally pivoting data (DataStage)
Specifying a vertical pivot operation (DataStage)
Specifying a vertical pivot operation and mapping output columns (DataStage)
Example of vertically pivoting data (DataStage)
Properties tab
Specifying execution options (DataStage)
Specifying where the stage runs (DataStage)
Specifying partitioning or collecting methods (DataStage)
Specifying a sort operation (DataStage)
Promote Subrecord
Examples (DataStage)
Example 1 (DataStage)
Example 2 (DataStage)
Fast path
Stage tab
Properties tab
Options section
Advanced tab
Remove Duplicates
Fast path
Stage tab
REST
Stage tab
Row Generator
Fast path
Stage tab
Output tab
Sample
Fast path
Stage tab
Link Ordering
Slowly Changing Dimension
Job design
Purpose codes
Surrogate keys
Editing
Defining the match condition
Selecting purpose codes
Purpose code definitions
Specifying information about a key source
Creating derivations for dimension columns
Dimension update action
Sort
Fast path
Stage tab
Split Subrecord
Fast path
Stage tab
Examples (DataStage)
Split Vector
Examples (DataStage)
Example 1 (DataStage)
Example 2 (DataStage)
Fast path
Stage tab
Properties tab
Options section
Advanced tab
Stored Procedure
Surrogate Key Generator
Creating the key source (DataStage)
Deleting the key source (DataStage)
Updating the state file (DataStage)
Generating surrogate keys (DataStage)
Switch
Example
Fast path
Stage tab
Tail
Fast path
Stage tab
Transformer
Basic concepts
Properties
Stage variables (DataStage)
Loop variables (DataStage)
Entering expressions (DataStage)
Loop example: converting a single row to multiple rows (DataStage)
Loop example: multiple repeating values in a single field (DataStage)
Loop example: generating new rows (DataStage)
Loop example: aggregating data (DataStage)
Surrogate Key tab (DataStage)
Link ordering (DataStage)
Triggers
Advanced (DataStage)
Input tab
Output tab
Runtime column propagation (DataStage)
System variables (DataStage)
Evaluation sequences for transformer expressions, stage variables, and loop variables (DataStage)
Reserved words
Parallel transform functions (DataStage)
Date and time functions (DataStage)
Logical functions (DataStage)
Mathematical functions (DataStage)
Null handling functions (DataStage)
Number functions (DataStage)
Raw functions (DataStage)
String functions (DataStage)
Retrieving substrings
Concatenating strings
Vector function (DataStage)
Type conversion functions (DataStage)
Utility functions (DataStage)
Operator functions (DataStage)
Wave Generator
Stage Tab
Properties
Input tab
Output tab
Web Service stage
Introduction to web services in DataStage
Encoding requests and responses
Required tasks in the Web Service stage
Other tasks
Setting up stage properties
Setting up input link properties
Setting up output link properties
Using a Web Service in DataStage
Write Range Map
Fast path
Stage tab
Input tab
XML Input
Stage tab
Transformation settings (DataStage)
XML Output
Using XML Output
About transforming tabular data
Validating documents and schemas
Aggregating input rows on output
Writing output to your file system
Processing NULLs and empty values
Selecting items for the XML Output
Setting the format of the XML output
Elements: Controlling the order and the repetition
Setting up stage properties
Setting up input and output link properties
DataStage connectors
Connecting to a data source in DataStage
Supported data sources in DataStage
Amazon RDS for PostgreSQL connector
Amazon S3 connector
Apache HDFS connector
Apache Hive connector
Apache Kafka connector
Apache Impala connector
FTP connector
Google BigQuery connector
Generic S3 connector
Greenplum connector
IBM Cloud Databases for PostgreSQL connector
IBM Data Virtualization Manager for z/OS connector
IBM Db2 for DataStage connector
IBM Db2 for z/OS connector
IBM Informix connector
IBM Master Data Management connector
Oracle Database for DataStage connector
PostgreSQL connector
Salesforce API for DataStage connector
Snowflake connector
Teradata connector
Teradata database for DataStage connector
File connectors in DataStage
Complex Flat File
Complex Flat File as a source
Defining record ID constraints in DataStage
Complex Flat File as a target in DataStage
Complex Flat File schema
Reject links in DataStage
Data set in DataStage
File set in DataStage
Input tab (DataStage)
Output tab (DataStage)
Lookup file set in DataStage
Sequential file in DataStage
Using Before/After SQL Statements
Before SQL (DataStage)
Before SQL (node) in DataStage
After SQL (DataStage)
After SQL (node) in DataStage
Using stored procedures
Syntax
Using multiple links
Common properties for DataStage connectors
Quality stages in DataStage
Designing match specifications
Adding passes
Match comparisons in DataStage
Reverse matching
ABS_DIFF comparison
AN_DINT comparison
AN_INTERVAL comparison
CHAR comparison
CNT_DIFF comparison
D_INT comparison
D_USPS comparison
DATE8 comparison
DELTA_PERCENT comparison
DISTANCE comparison
INT_TO_INT comparison
INTERVAL_NOPAR comparison
INTERVAL_PARITY comparison
LR_CHAR comparison
LR_UNCERT comparison
MULT_ALIGN comparison
MULT_EXACT comparison
MULT_RANGE comparison
MULT_UNCERT comparison
NAME_UNCERT comparison
NUMERIC comparison
PREFIX comparison
PRORATED comparison
TIME comparison
UNCERT comparison
Adding QSM_MAT_UNCERT_VERSION environment variable
USPS comparison
USPS_DINT comparison
USPS_INT comparison
Testing passes
Matching data in DataStage
How matching is done
Match types
Match column selection in DataStage
Match passes in DataStage
Blocking in DataStage
Weights and record comparisons
Investigate
Match Frequency
One-source Match
Two-source Match
Standardize
Standardize rule sets
Objects within rule sets
Classifications
Lookup tables
Output columns
Rules
Overrides
Quality stage pattern action reference
Introduction to the Pattern Action language
Parsing elements
Unconditional patterns
Identifying simple pattern classes
Conditional patterns
Simple conditional values
Conditional expressions
Using arithmetic expressions
Action statements
Copying information
Referencing dictionary fields from another rule set
Moving information
Concatenating information
Converting information
Retyping operands
Retyping multiple tokens
Patterning
Rule set extensions
User overrides for domain preprocessor rule sets
User overrides for rule sets
Setting margins
SOUNDEX phonetic coding
NYSIIS coding
Terminating pattern matching
Calling subroutines
Writing subroutines
Performing actions repetitively
Summary of sources and targets
Specifying your own stages
Defining build stages in DataStage
General tab
Properties tab
Build tab
Build stage macros
Informational macros (DataStage)
Flow-control macros (DataStage)
Input and output macros (DataStage)
Transfer Macros (DataStage)
How your code is executed (DataStage)
Inputs and outputs (DataStage)
Using multiple inputs (DataStage)
Example Build stage in DataStage
Header files
C++ classes - sorted by header file (DataStage)
C++ macros - sorted by header file (DataStage)
Defining custom stages
Compiling custom stages
Defining wrapped stages in DataStage
Creating a DataStage component
Message handlers
Defining data definitions
Reusable job design with subflows
Local subflows
Subflows
Parameters and parameter sets
Creating and using local parameters in DataStage
Creating and using parameter sets
Inserting parameters and parameter sets as properties in DataStage
Configuring runtime parameters in a flow
Configuring runtime parameters in a job
PROJDEF parameter set
Passing values from parameter sets into jobs by command-line interface
Environment variables
Managing environment variables
Guide to setting environment variables in DataStage
Buffering
Checkpoint
Compiler
Db2 Support
Debugging
Decimal support
Disk I/O
General Job Administration
Look up support
Miscellaneous
Network
NLS support
Oracle support
Partitioning
Reading and writing files environment variables in DataStage
Reporting environment variables in DataStage
SAS support
Sorting environment variables in DataStage
Sybase support environment variables in DataStage
Teradata support
Transport blocks
WLM
Partitioning and collecting data
Writing partitioned data in file-storage connectors
Running jobs
Settings for the project, flow, and job level
Setting up before-job and after-job subroutines
Cataloging a Db2 database in the runtime container
Scheduling DataStage jobs
Compile options with SQL Pushdown in DataStage
ELT run mode
ELT materialization policies in DataStage
Macros
Observing DataStage jobs
Migrating jobs
Migrating connections
Migrating a Teradata connection
Changing XML file locations after migration
Configuring the Hierarchical stage after migration in DataStage
Migrating BASIC routines
Migrating Web Service Transformer and Web Service Client stages
Asset import report (DataStage)
Downloading and importing flows
Development, testing, and production
Deployment spaces
DataStage Anywhere
Creating a remote engine
Managing a remote engine
Frequently asked questions for DataStage Anywhere
Security for remote engines with DataStage Anywhere
Sharing the existing remote engine across projects in watsonx.data integration
ODBC support for the remote engine
DataStage command-line tools
DataStage APIs
Orchestrating flows with Orchestration Pipelines
Pipeline components for DataStage
CEL expressions and limitations
Migrating and constructing pipeline flows
Referencing files in Bash node
Replacing BASIC routines
Examples
DataStage optimized runner
Storing and persisting metrics
Sharing DataStage artifacts with all IBM Cloud Object Storage containers
High availability and disaster recovery in DataStage
DevOps for DataStage
Managing assets
Getting started with Unit Testing
Configuring test data storage
Creating a DataStage test case
Capturing test data
Recapturing test result baseline
Editing a DataStage test case
DataStage specification format
Testing flow by using date/time references
Row count comparisons
Excluding columns from tests
Using Cluster Keys for high volume DataStage tests
Running a DataStage test case
Verifying a DataStage test results
Migrating test cases from older DataStage versions
Using the DataStage Assistant
Streaming real-time data
Administering StreamSets engines and environments
Understanding engine types
Engine version details
Data Collector engine versions
Data Collector 7.5.x engine details
7.5.x new features and enhancements
7.5.x upgrade impact
7.5.0 fixed issues
7.5.x known issue
Data Collector 7.4.x engine details
7.4.x new features and enhancements
7.4.x upgrade impact
7.4.0 fixed issues
7.4.x known issue
Data Collector 7.3.x engine details
7.3.x new features and enhancements
7.3.x upgrade impact
7.3.0 fixed issues
7.3.x known issue
Data Collector 7.2.x engine details
7.2.x new features and enhancements
7.2.x upgrade impact
7.2.x known issues
Jetstream engine versions
Jetstream 1.0.0 release notes
1.0.x new features and enhancements
1.0.x known issues
Creating a StreamSets environment
Environment configurations
Creating an environment
Running an engine
Prerequisites
Account prerequisites
Engine workstation prerequisites
Jetstream prerequisites
Running an engine with Docker or Podman
Running an engine with tunneling communication (default)
Running an engine with direct communication
Running an engine on Kubernetes with Helm (advanced)
Helm configurations
Running an engine on Kubernetes
Managing engine containers
Helm chart default values
Running multiple engines
Job failover guidelines
Customizing the engine command
Configuring environments
Stage libraries
Common stage libraries
Supported systems and versions
Cloud native
Protocols
Versioned systems
Data Collector configuration
Blocklist and allowlist for stage libraries
Configure Data Collector engine properties
Enabling HTTPS host verification
Prerequisite tasks
Step 1. Create a keystore file
Step 2. Configure engines to use the keystore file
Step 3. Mount the keystore file
Engine log configuration
Modifying the log level
Customizing the log configuration
Defining JVM options
Setting up external resources
External resource types
Archive structure
Setting up an archive
Updating an archive
Resource thresholds
CPU load
Memory
Running jobs
Defining resource thresholds
Install external libraries
Custom stage libraries
Including custom libraries in an external resource archive
Credential stores
Enabling credential stores
Configuring credential stores
Step 1. Install the credential store stage library
Step 2. Create the credential store properties file
Step 3. Configure credential store properties
Protecting sensitive data in credential store properties
Mounting local files and directories
AWS Secrets Manager properties
Azure Key Vault properties
CyberArk properties
Google Secret Manager properties
Hashicorp Vault properties
Java Keystore properties
Step 4. Mount the credential store properties file
Additional requirements and details
Azure Key Vault prerequisites
Google authentication requirement
Adding secrets to Java Keystore (Java only)
jks-credentialstore command reference (Java only)
Calling secrets from the flow
Defining custom CA certificates
Engine communication
Switching to direct communication
Monitoring engines
Viewing engine health and status
Monitoring online engines
Viewing engine logs
Generating support bundles
Accessing engine log files
Managing engines and environments
Freeing disk space on an engine workstation
Deleting engines from an environment
Deleting an environment
Upgrading engines
Upgrade an engine
Post upgrade tasks
Review Azure Synapse SQL flows
Upgrade from Oracle 11g release 2
Update Web Client stages that use signed JWT tokens
Create Kafka topics for Kafka Producer flows
Install a license certificate to connect to IBM Db2 for z/OS
Upgrade watsonx.data
Update flows that use unavailable stages
Update flows that use unavailable stage libraries
Review flows with Amazon stages and stages with an Amazon staging location
Review Pulsar flows
Update Snowflake targets that use the Use Snowflake Default Values property
Review SQL Server CDC Client and SQL Server Change Tracking sources
Review Azure Key Vault credential store configuration
Review Databricks cluster Java version
Review Databricks cluster storage configuration
Creating StreamSets flows
Flow concepts and design
Data in motion
Single and multithreaded flows
Delivery guarantee
Data Collector data types
Designing the data flow
Branching streams
Merging streams
Dropping unwanted records
Required fields
Preconditions
Error record handling
Flow error record handling
Stage error record handling
Example
Error records and version
Record header attributes
Working with header attributes
Internal attributes
Header attribute-generating stages
Record header attributes for record-based writes
Generating attributes for record-based writes
Field attributes
Working with field attributes
Field attribute-generating stages
Processing changed data
CRUD operation header attribute
Earlier implementations
CDC-enabled stages
Data changes in SQL Server or Azure SQL Database
CRUD-enabled stages
Processing the record
Use cases
Control character removal
Development stages
Shortcut keys for flow design
Understanding flow states
State transition examples
Technology preview features
Deprecated features
Flow configuration
Retrying the flow
Rate limit
Simple and bulk edit mode
Runtime values
Runtime resources
Step 1. Define runtime resources
Step 2. Call the runtime resource
Runtime properties
Step 1. Define runtime properties
Step 2. Call the runtime property
Parameters
Creating a parameter set
Adding a parameter set to a flow
Using parameters in a flow
Defining parameter values for a job
Event generation
Flow event records
SSL/TLS encryption
Keystore and truststore configuration
Local keystore and truststore
Remote keystore and truststore
Using a credential store
Transport protocols
Cipher suites
Connections
Connection types and support
Configuring a connection
Available Jetstream stages
Security in Amazon stages
Assume another role
Assume role methods
Create the trust policy
Configure stages to assume a role
Security in Google Cloud stages
Default credentials
Credentials in a file
Credentials in a property
Security in Kafka stages
Prerequisite tasks
SASL authentication credentials
Providing PLAIN credentials
Providing Kerberos credentials
Using a credential store
Enabling SSL/TLS encryption
Enabling SSL/TLS encryption and authentication
Enabling SASL authentication
Enabling SASL authentication on SSL/TLS
Enabling Confluent Cloud authentication
Enabling custom authentication
Kafka message keys
Storing message keys
Message key formats
String message keys
Avro message keys
Passing key values to Kafka
Example: Storing and passing Kafka message keys
SSL/TLS in CONNX stages
Authentication in Salesforce stages
Connected app with OAuth prerequisites
Considerations for IBM Connectivity Service stages
IBM Connectivity Service stage prerequisite
Troubleshooting IBM Connectivity Service
Connections
Connection types and support
Configuring a connection
Expression configuration
Basic syntax
Using field names in expressions
Field names with special characters
Referencing field names and field paths
Wildcard use for arrays and maps
Field path expressions
Supported stages
Field path expression syntax
Data type coercion
Flow validation
Configuring a flow
Configuring flow properties
Error record handling properties
Sources
Sources
Comparing Azure storage sources
Comparing HTTP sources
Comparing UDP Source sources
Comparing WebSocket sources
Batch size and wait time
Maximum record size
Amazon S3
Authentication method
Common prefix, prefix pattern, and wildcards
Multithreaded processing
Record header attributes
Object metadata in record header attributes
Read order
Buffer limit and error handling
Server side encryption
Event generation
Event records
Data formats
Configuring an Amazon S3 source
Amazon SQS Consumer
Authentication method
Queue name prefix
Multithreaded processing
Including SQS message attributes
Including sender attributes
Data formats
Configuring an Amazon SQS Consumer source
Aurora PostgreSQL CDC Client
Aurora PostgreSQL prerequisites
Enable logical replication
Assign the required role
JDBC driver
Schema, table name, and exclusion patterns
Initial change
Memory usage
SSL/TLS encryption
Record contents and generated records
Record header attributes
Sample records
Configuring an Aurora PostgreSQL CDC Client source
Azure Blob Storage
Prerequisites
Common path, path pattern, and wildcards
Read order
Buffer limit and error handling
Multithreaded processing
Record header attributes
Object metadata in record header attributes
Event generation
Event records
Data formats
Configuring an Azure Blob Storage source
Azure Data Lake Storage Gen2
Prerequisites
Retrieve authentication information
Common path, path pattern, and wildcards
Read order
Buffer limit and error handling
Multithreaded processing
Record header attributes
Object metadata in record header attributes
Event generation
Event records
Data formats
Configuring an Azure Data Lake Storage Gen2 source
Azure Data Lake Storage Gen2 (Legacy)
Prerequisites
Retrieve authentication information
File directory
File name pattern and mode
Read order
Multithreaded processing
Reading from subdirectories
Post-processing subdirectories
First file for processing
Record header attributes
Event generation
Event records
Buffer limit and error handling
Data formats
Configuring an Azure Data Lake Storage Gen2 (Legacy) source
Azure IoT/Event Hub Consumer
Storage account and container prerequisite
Resetting the source in Event Hub
Multithreaded processing
Data formats
Configuring an Azure IoT/Event Hub Consumer source
CoAP Server
Prerequisites
Multithreaded processing
Network configuration properties
Data formats
Configuring a CoAP Server source
Couchbase
Prerequisites
Offset
Event generation
Event record
Multithreaded processing
Configuring a Couchbase source
Directory
File name pattern and mode
Read order
Multithreaded processing
Reading from subdirectories
Post-processing subdirectories
First file for processing
Late directory
Record header attributes
Event generation
Event records
Buffer limit and error handling
Data formats
Configuring a Directory source
Elasticsearch
Security
Batch and incremental mode
Query
Incremental mode query
Scroll timeout
Multithreaded processing
Configuring an Elasticsearch source
File Tail
File processing and archived file names
Multiple paths and file sets
First file for processing
Late directories
Files matching a pattern - pattern constant
Record header attributes
Defining and using a tag
Multiple line processing
File Tail output
Event generation
Event records
Data formats
Configuring a File Tail source
Google BigQuery
Credentials
BigQuery data types
Datetime conversion
Event generation
Event record
Configuring a Google BigQuery source
Google Cloud Storage
Credentials
Common prefix, prefix pattern, and wildcards
Record header attributes
Event generation
Event records
Data formats
Configuring a Google Cloud Storage source
Google Pub/Sub Subscriber
Credentials
Multithreaded processing
Record header attributes
Data formats
Configuring a Google Pub/Sub Subscriber source
Groovy Scripting
Scripting objects
Multithreaded processing
Accessing record details
Type handling
Event generation
Event record
Record header attributes
Calling external Java code
Granting permissions on Groovy scripts
Configuring a Groovy Scripting source
HTTP Client
Processing mode
HTTP method
Headers
Per-status actions
Pagination
Page or offset number
Result field path
Keep all fields
Pagination examples
Example for link in HTTP header
Example for link in response field
Example for page number
Example for offset number
OAuth 2 authorization
Example for Twitter
Example for Microsoft Azure AD
Example for Google
Logging request and response data
Generated records
Data formats
Configuring an HTTP Client source
HTTP Server
Prerequisites
Send data to the listening port
Include the application ID in requests
Multithreaded processing
Data formats
Record header attributes
Configuring an HTTP Server source
IBM Db2
Prerequisites
Multithreaded processing
Record header attributes
Field attributes
IBM Db2 data types
Key column data types
Troubleshooting IBM Connectivity Service
Configuring an IBM Db2 source
JavaScript Scripting
Scripting objects
Multithreaded processing
Accessing record details
Type handling
Event generation
Event record
Record header attributes
Calling external Java code
Configuring a JavaScript Scripting source
JDBC Multitable Consumer
Database vendors and drivers
MySQL data types
Oracle data types
PostgreSQL data types
SQL Server data types
Unsupported data types
Installing the JDBC driver
Working with a MySQL JDBC driver
Table configuration
Schema, table name, and exclusion patterns
Offset column and value
Reading from views
Multithreaded processing modes
Multithreaded table processing
Multithreaded partition processing
Partition processing requirements
Multiple offset value handling
Best effort: Processing non-compliant tables
Non-incremental processing
Batch strategy
Process all available rows
Switch tables
Initial table order strategy
Processing queue
Multithreaded table processing only
Multithreaded partition processing only
Both multithreaded partition and table processing
JDBC attributes
JDBC header attributes
JDBC field attributes
Event generation
Event record
Configuring a JDBC Multitable Consumer source
JDBC Query Consumer
Database vendors and drivers
MySQL data types
Oracle data types
PostgreSQL data types
SQL Server data types
Unsupported data types
Installing the JDBC driver
Offset column and offset value
Full and incremental mode
Recovery
SQL query
SQL query for incremental mode
SQL query for full mode
Stored procedure in full mode
JDBC attributes
JDBC header attributes
JDBC field attributes
Event generation
Event record
Configuring a JDBC Query Consumer source
Jira
Event generation
Event records
OAuth 2 authentication
Configuring a Jira source
JMS Consumer
Installing JMS drivers
Additional JMS properties
Working with TIBCO EMS
Configuring for TIBCO and SSL
Data formats
Configuring a JMS Consumer source
Jython Scripting
Scripting objects
Thread safety in Jython scripts
Multithreaded processing
Accessing record details
Type handling
Event generation
Event record
Record header attributes
Calling external Java code
Configuring a Jython Scripting source
Kafka Multitopic Consumer
Offset management
Multithreaded processing
Additional Kafka properties
Record header attributes
Kafka security
Data formats
Configuring a Kafka Multitopic Consumer source
Kinesis Consumer
Multithreaded processing
Authentication method
Additional Kinesis properties
Read interval
Lease table tags
Resetting the Kinesis Consumer source
Data formats
Reading from DynamoDB or CloudWatch
Configuring a Kinesis Consumer source
MongoDB Atlas
Credentials
Offset field and initial offset
Specifying field paths
Read preference
Custom filter
Event generation
Event records
Enabling SSL/TLS
MongoDB data types
Reading BSON types
Configuring a MongoDB Atlas source
MongoDB Atlas CDC
Credentials
Read preferences
Generated records
CRUD operation and CDC header attributes
Enabling SSL/TLS
MongoDB data types
Reading BSON types
Configuring a MongoDB Atlas CDC source
MQTT Subscriber
Topics
Record header attributes
Data formats
Configuring an MQTT Subscriber source
MySQL Binary Log
Prerequisites
Configure MySQL Server for row-based logging
Enable the required authentication
Set the row metadata property
Install the JDBC driver
Initial offset
Generated records
Processing generated records
Tables to include or ignore
MySQL data types
Configuring a MySQL Binary Log source
OPC UA Client
Processing mode
Providing NodeIds
Security
Configuring an OPC UA Client source
Oracle Bulkload
Prerequisite
Static and non-static tables
Batch processing
Schema and table names
Multithreaded processing
Field attributes
Event generation
Event record
Configuring an Oracle Bulkload source
Oracle CDC
Comparing Oracle CDC sources
Updating Oracle CDC Client flows
Prerequisites
Task 1. Configure the database archiving mode
Task 2. Enable supplemental logging
Task 3. Create a user account
Task 4. Install required libraries on Data Collector
Primary and standby databases
Table filters
Start mode
Record formats
Custom record options
Parse SQL statements, supported operations, and record attributes
CRUD operation header attributes
CDC header attributes
Other header attributes
Default field attributes
Annotation field attributes
Multithreaded parsing
Query fetch size
Uncommitted transaction handling
Evicted transaction handling
Event generation
Event records
Oracle data types
Unsupported data types
Data preview with Oracle CDC
Configuring an Oracle CDC source
Oracle CDC Client
LogMiner dictionary source
Oracle CDC Client prerequisites
Task 1. Enable database archiving mode
Task 2. Enable supplemental loggingIf you change this title, update the text reference in Task 1.
Task 3. Create a user accountIf you change this title, update the text reference in Task 2.
Task 4. Extract a LogMiner dictionary (redo logs)
Task 5. Install the driver
Available parsers
Table configuration
Schema, table name, and exclusion patterns
Initial change
Choosing buffers
Local buffer resource requirements
Uncommitted transaction handling
JDBC fetch options
Include nulls
Unsupported data types
Conditional data type support
Processing Blob and Clob columns
Parse SQL, supported operations, and generated records
CRUD operation header attributes
CDC header attributes
Other header attributes
Field attributes
Database time zone
Change in daylight saving time
Event generation
Event records
Multithreaded parsing
Working with the SQL Parser processor
Data preview with Oracle CDC Client
Configuring an Oracle CDC Client source
Oracle Multitable Consumer
Prerequisite
Oracle data types
Unsupported data types
Table configuration
Schema, table name, and exclusion patterns
Offset column and value
Multithreaded processing modes
Multithreaded table processing
Multithreaded partition processing
Partition processing requirements
Multiple offset value handling
Best effort: Processing non-compliant tables
Non-incremental processing
Batch strategy
Process all available rows
Switch tables
Initial table order strategy
Processing queue
Multithreaded table processing only
Multithreaded partition processing only
Both multithreaded partition and table processing
Generated records
CRUD operation header attributes
JDBC header attributes
JDBC field attributes
Event generation
Event records
Configuring an Oracle Multitable Consumer source
Oracle XStream
Oracle prerequisites
Requirements
Command tools and syntax
Task 1. Set database parameters
Task 2. Create the CDC user
Task 3. Create the outbound server (existing components only)
Include all tables
Include specified tables
Task 4. Start the outbound server (existing components only)
Task 5. Prepare the database and tables
Task 6. Run verification commands
Data Collector prerequisite
Operation mode
Start mode
CRUD operation header attributes
CDC header attributes
Field attributes
Event generation
Event records
Configuring an Oracle XStream source
PostgreSQL CDC Client
PostgreSQL prerequisites
Install the logical decoder
Assign the required role
JDBC driver
Schema, table name, and exclusion patterns
Initial change
Memory usage
SSL/TLS encryption
Record contents and generated record
Record header attributes
Sample records
Configuring a PostgreSQL CDC Client source
Pulsar Consumer
Topics selector
Multithreaded processing
Offset management
Record header attributes
Schema properties
Security
Enabling TLS transport encryption
Enabling TLS authentication
Enabling JWT authentication
Enabling OAuth authentication
Data formats
Configuring a Pulsar Consumer source
Pulsar Consumer (Legacy)
Topics selector
Parallel reads of a topic
Offset management
Record header attributes
Schema properties
Security
Enabling TLS transport encryption
Enabling TLS authentication
Enabling JWT authentication
Enabling OAuth authentication
Data formats
Configuring a Pulsar Consumer (Legacy) source
RabbitMQ Consumer
Queue
Record header attributes
Data formats
Configuring a RabbitMQ Consumer source
Redis Consumer
Channels and patterns
Data formats
Configuring a Redis Consumer source
REST Service
HTTP listening port
API gateway
Gateway authentication
REST API URLs
Required request header
Security
Using application IDs
REST API client requirement
Multithreaded processing
Generated response
Sample responses
Record header attributes
Data formats
Configuring a REST Service source
Salesforce
Querying data
Using the SOAP and Bulk API
Bulk API example
Aggregate functions in SOQL queries
Using the Bulk API with PK Chunking
PK chunking example
Repeat query
Processing deleted records
Subscribing to notifications
Processing PushTopic events
PushTopic event record format
Processing platform events
Processing change events
Reading custom objects or fields
Salesforce attributes
Salesforce header attributes
CRUD operation header attribute
Salesforce field attributes
Event generation
Event record
Changing the API version
Configuring a Salesforce source
Salesforce Bulk API 2.0
Querying data
Bulk API 2.0 queries
Full and incremental mode
Multithreaded processing
Processing deleted records
Reading custom objects or fields
Salesforce attributes
Salesforce header attribute
Salesforce field attributes
Event generation
Event record
Changing the API version
Configuring a Salesforce Bulk API 2.0 source
SAP HANA Query Consumer
Installing the JDBC driver
Offset column and offset value
Full and incremental mode
Recovery
SQL query
SQL query for incremental mode
SQL query for full mode
JDBC attributes
JDBC header attributes
JDBC field attributes
SAP HANA header attributes
Event generation
Event record
Configuring an SAP HANA Query Consumer source
SFTP/FTP/FTPS Client
File name pattern and mode
Read order
First file for processing
Credentials
Record header attributes
Event generation
Event records
Post processing
Data formats
Configuring an SFTP/FTP/FTPS Client source
Snowflake Bulk
Prerequisites
Create a Snowflake stage
AWS credentials
Google Cloud Storage credentials
Assign privileges
Batch processing
Define a role
Multithreaded processing
Table configurations
Error handling
Record header attributes
Snowflake data types
Configuring a Snowflake Bulk source
SQL Server CDC Client
JDBC driver
Supported operations
Time windows
Table configuration
Initial table order strategy
Allow late table processing
Checking for schema changes
Generated record
Record header attributes
CRUD operation header attributes
Field attributes
Event generation
Event record
Configuring a SQL Server CDC Client source
SQL Server Change Tracking
JDBC driver
Prerequisites
Enable change tracking
Assign permissions
Table configuration
Initial table order strategy
Generated record
Record header attributes
CRUD operation header attributes
Field attributes
Event generation
Event record
Configuring a SQL Server Change Tracking source
TCP Server
Multithreaded processing
Closing connections for invalid data
Sending acknowledgements
Using expressions in messages
TCP modes
Data formats
Configuring a TCP Server source
UDP Multithreaded Source
Processing raw data
Receiver and worker threads
Packet queue
Multithreaded flows
Metrics for performance tuning
Configuring a UDP Multithreaded Source
UDP Source
Processing raw data
Receiver threads
Configuring a UDP Source
Web Client
Ingestion mode
HTTP method
Expression method
Headers
Grouping style
Event generation
Event records
Per-status actions
Per-timeout actions
Pagination
Page or offset number
OAuth 2 authentication
Generated records
Data formats
Configuring a Web Client source
WebSocket Client
Read REST response data from Data Collector
Generated microservice responses
Sample responses
Data formats
Configuring a WebSocket Client source
WebSocket Server
Prerequisites
Send data to the listening port
Include the application ID in requests
Multithreaded processing
Generated microservice responses
Sample responses
Data formats
Configuring a WebSocket Server source
Processors
Processors
Base64 Field Decoder
Configuring a Base64 Field Decoder processor
Base64 Field Encoder
Configuring a Base64 Field Encoder processor
Couchbase Lookup
Record header attributes
Configuring a Couchbase Lookup processor
Data Generator
Target field
Data formats
Configuring a Data Generator processor
Data Parser
Data formats
Configuring a Data Parser processor
Delay
Configuring a Delay processor
Encrypt and Decrypt Fields
Supported data types
Key provider
AWS credentials
Cipher suite
Encryption contexts
Data key caching
Encrypt and decrypt records
Configuring an Encrypt and Decrypt Field processor
Expression Evaluator
Output fields and attributes
Record header attribute expressions
Field attribute expressions
Configuring an Expression Evaluator processor
Field Flattener
Flatten the entire record
Flatten specific fields
Configuring a Field Flattener processor
Field Hasher
Hash methods
Field separator
List, map, and list-map fields
Configuring a Field Hasher processor
Field Mapper
Field values
Field names
Field paths
Aggregation expressions
Configuring a Field Mapper processor
Field Masker
Mask types
Configuring a Field Masker processor
Field Merger
Configuring a Field Merger processor
Field Order
Missing and extra fields
Configuring a Field Order processor
Field Pivoter
Generated records
Configuring a Field Pivoter processor
Field Remover
Configuring a Field Remover processor
Field Renamer
Renaming sets of fields
Configuring a Field Renamer processor
Field Replacer
Replacing values with nulls
Replacing values with new values
Data types for conditional replacement
Configuring a Field Replacer processor
Field Splitter
Not enough splits
Too many splits
Example
Configuring a Field Splitter processor
Field Type Converter
Valid type conversions
Expressions to convert by field name
Changing the scale of decimal fields
Configuring a Field Type Converter processor
Field Zip
Merging List data
Merging List-Map data
Pivoting merged lists
Configuring a Field Zip processor
Geo IP
Supported databases
Database file location
GeoIP field types
Full JSON field types
Configuring a Geo IP processor
Groovy Evaluator
Processing mode
Groovy scripting objects
Accessing record details
Processing list-map data
Type handling
Event generation
Working with record header attributes
Accessing whole file format records
Calling external Java code
Granting permissions on Groovy scripts
Configuring a Groovy Evaluator processor
HTTP Client
HTTP method
Expression method
Headers
Per-status actions
Pass records after retry or timeout failures
Record header attributes for passed records
Pagination
Page or offset number
Result field path
Keep all fields
Pagination examples
Example for link in HTTP header
Example for link in response field
Example for page number
Example for offset number
OAuth 2 authorization
Example for Twitter
Example for Microsoft Azure AD
Example for Google
Generated output
Response headers
Logging request and response data
Logging the resolved resource URL
Data formats
Configuring an HTTP Client processor
HTTP Router
Configuring an HTTP Router processor
JavaScript Evaluator
Processing mode
JavaScript scripting objects
Accessing record details
Processing list-map data
Type handling
Event generation
Working with record header attributes
Accessing whole file format records
Calling external Java code
Configuring a JavaScript Evaluator processor
JDBC Lookup
Database vendors and drivers
MySQL data types
Oracle data types
PostgreSQL data types
SQL Server data types
Unsupported data types
Installing the JDBC driver
Lookup cache
Using additional threads
Retry lookups for missing values
JDBC field attributes
Configuring a JDBC Lookup processor
JDBC Tee
Database vendors and drivers
MySQL data types
PostgreSQL data types
Installing the JDBC driver
CRUD operation processing
Single and multi-row operations
Configuring a JDBC Tee processor
JSON Generator
Configuring a JSON Generator processor
JSON Parser
Configuring a JSON Parser processor
Jython Evaluator
Processing mode
Jython scripting objects
Accessing record details
Processing list-map data
Type handling
Event generation
Working with record header attributes
Accessing whole file format records
Calling external Java code
Calling an external Python module
Configuring a Jython Evaluator processor
Log Parser
Log formats
Configuring a Log Parser processor
MLeap Evaluator
Prerequisites
MLeap model as a microservice
Example: Airbnb model
Configuring an MLeap Evaluator processor
MongoDB Atlas Lookup
Field mappings
Lookup cache
Credentials
Read preference
Configuring a MongoDB Atlas Lookup processor
PMML Evaluator
Prerequisites
Installing the PMML stage library
PMML model as a microservice
Example: Iris classification
Configuring a PMML Evaluator processor
PostgreSQL Metadata
JDBC driver
Schema and table names
Decimal precision and scale field attributes
Caching information
PostgreSQL data types
Configuring a PostgreSQL Metadata processor
Record Deduplicator
Comparison window
Configuring a Record Deduplicator processor
Redis Lookup
Data types
Lookup cache
Configuring a Redis Lookup processor
Salesforce Bulk API 2.0 Lookup
Lookup cache
Salesforce attributes
Changing the API version
Configuring a Salesforce Bulk API 2.0 Lookup processor
Salesforce Lookup
Lookup mode
Aggregate functions in SOQL queries
Lookup cache
Salesforce attributes
Changing the API version
Configuring a Salesforce Lookup processor
Schema Generator
Using schema header attributes
Generated schemas
Caching schemas
Configuring a Schema Generator processor
SQL Parser
Using multiple flows
Example
Resolving the schema
Unsupported data types
Generated records
CRUD operation header attributes
CDC header attributes
Other header attributes
Field attributes
Configuring an SQL Parser processor
Static Lookup
Configuring a Static Lookup processor
Stream Selector
Default stream
Sample conditions for streams
Configuring a Stream Selector processor
TensorFlow Evaluator
Prerequisites
Evaluation method
Event generation
Event records
Serving a TensorFlow model
Configuring a TensorFlow Evaluator processor
Web Client
Comparing Web Client and HTTP Client processors
HTTP method
Expression method
Headers
Grouping style
Event generation
Event records
Per-status actions
Per-timeout actions
Pagination
Page or offset number
OAuth 2 authentication
Generated output
Data formats
Configuring a Web Client processor
Whole File Transformer
Implementation overview
Write Avro flow
Parquet conversion flow
Memory and storage requirements
Generated record
Implementation example: Amazon S3 Parquet conversion
Write Avro flow example
Parquet conversion flow example
Runtime
Configuring a Whole File Transformer processor
Windowing Aggregator
Window type, time windows, and information display
Rolling windows
Sliding windows
Calculation components
Aggregate functions
Event generation
Event record root field
Event records
Monitoring aggregations
Configuring a Windowing Aggregator processor
XML Flattener
Generated records
Configuring an XML Flattener processor
XML Parser
Configuring an XML Parser processor
Targets
Targets
Amazon S3
Authentication method
Bucket
Partition prefix
Time basis and data time zone for time-based buckets and partition prefixes
Object names
Whole file names
Add tags to objects
Event generation
Event records
Server-side encryption
Data formats
Configuring an Amazon S3 target
Apache Iceberg for AWS
AWS Prerequisites
Creating the Iceberg table
Partitioning a new table
Write mode
Schema evolution mode
Supported type promotions
Amazon server-side encryption
Processing timestamp data
Iceberg data types
Configuring an Apache Iceberg for AWS target
Azure Blob Storage
Prerequisite
Blob types
Event generation
Event records
Data formats
Configuring an Azure Blob Storage target
Azure Data Lake Storage Gen2
Prerequisites
Retrieve authentication information
Directory templates
Time basis
Late records and late record handling
Timeout to close idle files
Recovery
Event generation
Event records
Resolving out of memory errors
Data formats
Configuring an Azure Data Lake Storage Gen2 target
Azure Event Hub Producer
Data formats
Configuring an Azure Event Hub Producer target
Azure IoT Hub Producer
Register Data Collector as an IoT Hub device
Data formats
Configuring an Azure IoT Hub Producer target
Azure Synapse SQL
Prerequisites
Prepare the Azure Synapse instance
Prepare the Azure Storage staging area
Enable access to the container
Load methods
Connections and authentication
Azure Synapse connection
Staging connection
Copy statement connection
Specifying tables
Enabling data drift handling
Row generation
Missing fields and fields with invalid types
Performance optimization
Azure Synapse data types
CRUD operation processing
Configuring an Azure Synapse SQL target
Cassandra
Batch type
Authentication
Kerberos (DSE) authentication
Cassandra data types
Configuring a Cassandra target
CoAP Client
Data formats
Configuring a CoAP Client target
Couchbase
CRUD operation processing
Compare and swap
Data formats
Configuring a Couchbase target
Databricks
Prerequisite
Load methods
CRUD operation processing
Primary key location
Specifying tables
Enabling data drift handling
Partitioning tables
Performance optimization
Staging location
Amazon S3 credentials
ADLS Gen2 authentication information
Google Cloud credentials
Row generation
Missing fields and fields with invalid types
Databricks data types
Configuring a Databricks target
Elasticsearch
Security
Time basis and time-based indexes
Document IDs
CRUD operation processing
Configuring an Elasticsearch target
Google BigQuery
Prerequisites
Prepare the Google BigQuery data warehouse
Prepare the Google Cloud Storage staging area
Credentials
Staging file formats
Specifying datasets and tables
Enabling data drift handling
Partitioning new tables
Partition configurations
Partition options
Row generation
Missing fields and fields with invalid types
Performance optimization
CRUD operation processing
BigQuery data types
Configuring a Google BigQuery target
Google Bigtable
Prerequisites
Install the BoringSSL library
Configure credentials
Row key
Cloud Bigtable data types
Column family and field mappings
Time basis
Configuring a Google Bigtable target
Google Cloud Storage
Credentials
Partition prefix
Time basis, data time zone, and time-based partition prefixes
Object names
Whole file names
Event generation
Event records
Data formats
Configuring a Google Cloud Storage target
Google Pub/Sub Publisher
Credentials
Data formats
Configuring a Google Pub/Sub Publisher target
HTTP Client
HTTP method
Expression method
Headers
Number of requests
Logging request and response data
Send microservice responses
OAuth 2 authorization
Example for Twitter
Example for Microsoft Azure AD
Example for Google
Data formats
Configuring an HTTP Client target
IBM Cloud Object Storage
Prerequisite
Bucket
Troubleshooting IBM Connectivity Service
Configuring an IBM Cloud Object Storage target
IBM Db2
Prerequisites
Specifying tables
Key columns
IBM Db2 data types
Troubleshooting IBM Connectivity Service
Configuring an IBM Db2 target
IBM watsonx.data
Prerequisite
Specifying tables
Creating tables
watsonx.data data types
Troubleshooting IBM Connectivity Service
Configuring an IBM watsonx.data target
InfluxDB 2.x
Configuring an InfluxDB 2.x target
JDBC Producer
Database vendors and drivers
Installing the JDBC driver
CRUD operation processing
Update and delete operations
Single and multi-row operations
Configuring a JDBC Producer target
Jira
Event generation
Event records
OAuth 2 authentication
Configuring a Jira target
JMS Producer
Installing JMS drivers
Include headers
Additional JMS properties
Working with TIBCO EMS
Configuring for TIBCO and SSL
Data formats
Configuring a JMS Producer target
Kafka Producer
Broker list
Runtime topic resolution
Partition strategy
Send microservice responses
Additional Kafka properties
Writing Kafka message headers
Kafka security
Data formats
Configuring a Kafka Producer target
Kinesis Firehose
Authentication method
Delivery stream
Data formats
Configuring a Kinesis Firehose target
Kinesis Producer
Authentication method
Additional Kinesis properties
Send Microservice responses
Data formats
Configuring a Kinesis Producer target
Local FS
Directory templates
Time basis
Late records and late record handling
Timeout to close idle files
Recovery
Event generation
Event records
Data formats
Configuring a Local FS target
MongoDB Atlas
Credentials
Specifying field paths
Unordered writes and stopping the flow
Define the CRUD operation
Performing upserts
Enabling SSL/TLS
MongoDB data types
Writing BSON types
Configuring a MongoDB Atlas target
MQTT Publisher
Topic
Data formats
Configuring an MQTT Publisher target
Named Pipe
Prerequisites
Create the named pipe
Configure the named pipe reader
Working with the named pipe reader
Data formats
Configuring a named pipe target
Oracle
Prerequisite
Enabling data drift handling
Generated data types
Creating tables
CRUD operation processing
Configuring an Oracle target
Pulsar Producer
Schema properties
Security
Enabling TLS transport encryption
Enabling TLS authentication
Enabling JWT authentication
Enabling OAuth authentication
Data formats
Configuring a Pulsar Producer target
RabbitMQ Producer
Queue
Data formats
Configuring a RabbitMQ Producer target
Redis
Mode
Data types for batch mode
Data formats for publish mode
Define the CRUD operation
Configuring a Redis target
Salesforce
CRUD operation processing
Hard deleting records
Field mappings
Changing the API version
Configuring a Salesforce target
Salesforce Bulk API 2.0
CRUD operation processing
Hard deleting records
Field mappings
Changing the API version
Configuring a Salesforce Bulk API 2.0 Target
Send Response to Source
Configuring a Send Response to Source target
SFTP/FTP/FTPS Client
Credentials
Event generation
Event records
Data format
Configuring an SFTP/FTP/FTPS Client target
SingleStore
CRUD operation processing
Configuring a SingleStore target
Snowflake
Sample use case
Prerequisites
Create a Snowflake stage
AWS credentials
Google Cloud Storage credentials
DESCRIBE prerequisite
COPY prerequisites
Snowpipe prerequisites
MERGE prerequisites
Implementation notes
Load methods
Primary key location
Error handling
Define a role
Performance optimization
Row generation
Specifying tables
Enabling data drift handling
Generated data types
Creating tables
CRUD operation processing
Configuring a Snowflake target
Snowflake File Uploader
Prerequisites
Create an internal Snowflake stage (optional)
Assign required privileges
Implementation notes
Define a role
Event generation
Event records
Configuring a Snowflake File Uploader target
Splunk
Prerequisites
Required record format
Logging request and response data
Configuring a Splunk target
Syslog
Protocol
Using SSL/TLS
Enabling SSL
Message content
Data formats
Configuring a Syslog target
Tableau CRM
Changing the API version
Define the operation
Metadata JSON
Automatic recovery
Manual upload recovery
Configuring an Tableau CRM target
Teradata
Prerequisites
Installing the Teradata driver
COPY prerequisites
MERGE prerequisites
Load methods
Primary key location
Performance optimization
Specifying tables
Enabling data drift handling
Generated data types
Creating tables
Staging location
Amazon S3 credentials
Azure authentication information
Google Cloud credentials
Row generation
Missing fields and fields with invalid types
CRUD operation processing
Configuring a Teradata target
To Error
Trash
Web Client
Comparing Web Client and HTTP Client targets
HTTP method
Expression method
Headers
Grouping style
Event generation
Event records
Per-status actions
Per-timeout actions
Pagination
Page or offset number
OAuth 2 authentication
Data formats
Configuring a Web Client target
WebSocket Client
Data formats
Configuring a WebSocket Client target
Executors
Executors
ADLS Gen2 File Metadata
Prerequisites
Retrieve authentication information
Related event generating stages
Changing metadata
Specifying the file path
Changing the file name or location
Defining the owner, group, permissions, and ACLs
Creating an empty file
Removing a file or directory
Event generation
Event records
Configuring an ADLS Gen2 File Metadata executor
Amazon S3
Authentication method
Create new objects
Copy objects
Tag existing objects
Event generation
Event records
Server-side encryption
Configuring an Amazon S3 executor
Databricks Job Launcher
Prerequisites
Event generation
Event records
Monitoring
Configuring a Databricks Job Launcher executor
Databricks Query
Prerequisite
Spark SQL queries
Storage connection
ADLS Gen2 authentication information
Event generation
Event records
Configuring a Databricks Query executor
Email
Prerequisite
Conditions
Using expressions
Configuring an Email executor
Google Cloud Storage
Credentials
Create new objects
Copy or move objects
Set metadata
Event generation
Event records
Configuring a Google Cloud Storage executor
Google BigQuery
Prerequisite
Credentials
SQL queries
Event generation
Event records
Configuring a Google BigQuery executor
JDBC Query
Database vendors and drivers
Installing the JDBC driver
SQL queries
Event generation
Event records
Configuring a JDBC Query executor
Pipeline Finisher
Recommended implementation
Related event generating stages
Source reset for additional flow runs
Notification options
Configuring a Pipeline Finisher executor
SFTP/FTP/FTPS Client
Credentials
Configuring an SFTP/FTP/FTPS Client executor
Shell
Data Collector shell impersonation mode
Script configuration
Configuring a Shell executor
Snowflake
Prerequisite
Implementation notes
Snowflake File Uploader and executor flows
Define a role
SQL queries
Event generation
Event record
Configuring a Snowflake executor
Working with flows
Previewing a flow
Views
Preview data types
Writing to targets and executors
Modifying preview properties
Additional preview details
Downloading and importing flows
Downloading flows
Downloading multiple flows
Downloading a single flow from the canvas
Importing a flow
Dataflow triggers
Dataflow triggers overview
Flow event generation
Using flow events
Pass to an executor
Stage event generation
Using stage events
Task execution streams
Event storage streams
Executors
Logical pairings
Event records
Event record header attributes
Summary
Solutions
Solutions overview
Stopping a flow after processing all available data
Sending email during flow processing
Preserving an audit trail of events
Loading data into Databricks Delta Lake
Bulk loading data into a Delta Lake table
Create the flow and configure the Salesforce source
Configure the Expression Evaluator processor
Configure the target to bulk load data
Run the flow to bulk load data
Merging changed data into a Delta Lake table
Create the flow and configure the MySQL Binary Log source
Configure processors to restructure the record
Configure the target to merge changed data
Run the flow to merge changed data
Drift Synchronization Solution for PostgreSQL
Basic implementation and processing
Flattening records
Requirements
Implementation steps
Case study
JDBC Multitable Consumer source
PostgreSQL Metadata processor
JDBC Producer target
Running the flow
PostgreSQL data types
Data formats
Data formats overview
File compression formats
Avro data format
Reading Avro data
Writing Avro data
Binary data format
Datagram data format
Delimited data format
Reading delimited data
CSV parser
Delimited data root field type
Writing delimited data
Excel data format
Log data format
NetFlow data processing
Caching NetFlow 9 templates
NetFlow 5 generated records
NetFlow 9 generated records
Parquet data format
Reading Parquet data
Writing Parquet data
Protobuf data format prerequisites
SDC record data format
Text data format with custom delimiters
Processing XML data with custom delimiters
Whole file data format
Basic flow
Whole file records
Processors for file reference information
Defining the transfer rate
Writing whole files
Access permissions
Including checksums in events
Reading and processing XML data
Creating multiple records with an XML element
Using XML elements with namespaces
Creating multiple records with an XPath expression
Using XPath expressions with namespaces
Simplified XPath syntax
Sample XPath expressions
Predicates in XPath expressions
Predicate examples
Preserving the root element
Including field XPaths and namespaces
XML attributes and namespace declarations
Parsed XML
Writing XML data
Record structure requirement
Multithreaded flows
Multithreaded flow overview
How it works
Sources for multithreaded flows
Processor caching
Tuning threads and runners
Resource usage
Multithreaded flow summary
Microservice flows
Microservice flows overview
Stages for microservice flows
Microservice sources
Microservice targets
Sample flow
Creating a microservice flow
Data formats by stage
Data format support
Sources
Processors
Targets
Expression language
Expression language
Expression completion in properties
Tips for expression completion
Expression examples
Functions
Record functions
Delimited data record functions
Error record functions
Base64 functions
Credential functions
Data generation functions
Faker functions
Xeger functions
Field functions
File functions
Flow functions
Math functions
String functions
Time functions
Timestamp functions
Miscellaneous functions
Constants
Datetime variables
Literals
Operators
Operator precedence
Reserved words
Regular expressions
Regular expressions overview
Regular expressions in the flow
Quick reference
Regex examples
Grok patterns
Defining grok patterns
General grok patterns
Date and time grok patterns
Java grok patterns
Log grok patterns
Networking grok patterns
Path grok patterns
Troubleshooting
Accessing error messages
Flow basics
General validation errors
Sources
Directory
Elasticsearch
JDBC sources
Oracle CDC Client
PostgreSQL CDC Client
Salesforce
Scripting sources
SQL Server CDC Client
Processors
Encrypt and Decrypt Fields
Targets
Azure Data Lake Storage
Cassandra
Elasticsearch target
Kafka Producer
JDBC connections
No suitable driver
Cannot connect to database
MySQL JDBC driver and time values
Performance
Running StreamSets jobs
Managing jobs and job runs
Monitoring job runs
Reviewing metrics
Tracking history
Viewing log messages
Capturing snapshots
Managing job offsets
Sources that maintain offsets
Viewing the job offset
Resetting the job offset
Orchestrating jobs with Orchestration Pipelines
Replicating data
Running replication jobs
Supported Data Replication connections
Replicating Amazon RDS for PostgreSQL data
Supported PostgreSQL data types
Replicating Apache Kafka data
Replicating IBM Db2 data
Supported IBM Db2 data types
Replicating IBM Db2 on Cloud data
Supported IBM Db2 on Cloud data types
Replicating IBM Db2 Warehouse data
Replicating PostgreSQL data
Choosing a business goal
Configuring the Change Log business goal
Change Log types
Change Log tables
Monitoring replication jobs
Managing replication jobs
Observing your data
Data Observability issue detection and remediation
Data Observability alerts
Creating alerts
Receiving alerts in external applications
Creating a Slack alert receiver
Creating a Microsoft Teams alert receiver
Creating a PagerDuty alert receiver
Roles and permissions in Data Observability
Using Data Observability
Setting up watsonx.data integration and configuring accounts
Accessing Data Observability
Analyzing detected issues, creating alerts and alert receivers
Creating threshold alerts with dynamic ranges
Analyzing triggered alerts
Integrating data with an agent
Setting up a project for an agent
Integrating data with Data Integration Agent
Integrating data with the MCP server
Configuring Claude Desktop
Configuring IBM Bob
Data products
Managing Data Product Hub
Managing storage
Managing the community
Managing business domains
Managing connections
Understanding credentials for connections
Managing custom properties
Managing data contracts
Understanding data contract fields
Managing approval processes
Workflow template properties
Discovering data products
Managing your task inbox as a consumer
Requesting a new data product
Searching for data products
Subscribing to a data product
Subscribing to a data product that requires approval
Flight client example for accessing a data product
Publishing a data product
Managing your task inbox as a producer
Managing your Insights dashboard
Creating a data product
Creating a data product from a catalog
Creating a data product from a project
Creating a data product directly from a source
Creating a data product from a URL
Creating a data product from a YAML file
Creating a data product from SQL
Creating a data product from a query
Creating a data product from a customizable query
Creating a data product from a complex query
Creating a data product from a custom delivery method
Best practices for creating a data product
Supported connectors for data products
Managing the lifecycle of data products
Working with delivery methods
Creating a custom delivery method
Delivery methods for connectors
Data governance
Planning to implement data governance
Planning to set up data cataloging and governance
Planning to implement a governance framework
Planning to protect data with rules
Planning to author data protection rules
Planning to curate data
Planning to monitor IBM watsonx.data intelligence
Managing IBM watsonx.data intelligence
Monitoring with Governance insights dashboards
Assigning roles and permissions for users
Custom properties, relationships, and asset types
Creating custom asset types
Creating custom properties
Creating custom relationships
Importing custom properties or relationships from a file
Managing custom properties, relationships, and asset types
Managing rule settings
Migrating data protection rules
Managing workflows for governance artifacts
Configuring workflows for data quality SLAs
Working with data quality remediation tasks
Monitoring workflow tasks
Detecting anomalies in workflows by using IBM Databand
Setting up reporting for IBM watsonx.data intelligence
Database requirements
Data model
Managing reporting
Sample reporting queries
Reporting tables
Workspaces
Asset relationships
Categories
Governance artifacts
Artifact relationships
Data quality rules
Customizations
Workflow
User Profiles
Tags
Rules
Metadata imports and enrichments
Catalogs
Administering a catalog
Creating a catalog
Duplicate asset handling
Managing access to a catalog
Catalog collaborator roles
Accessing orphaned catalogs
Changing catalog settings
Deleting a catalog
Saving searches for catalog assets
Catalog assets
Finding and viewing an asset in a catalog
Browsing asset hierarchies
Adding assets to a catalog
Adding a data file
Adding a connection
Adding data from a connection
Adding a connected folder asset from a connection
Adding COBOL copybook assets
Importing and exporting assets and asset metadata with a CSV file
CSV file format for importing and exporting asset metadata
CSV file format for importing and exporting asset relationships
Downloading data assets
Editing asset properties
Relationships in a catalog
Asset relationships
Managing relationships in a catalog
Exploring relationships
Controlling access to an asset
Profiling an asset
Removing an asset
Governance artifacts
Finding and viewing governance artifacts
Tags
Governance artifact properties
Versioning of governance artifacts
Managing governance artifacts
Import methods for governance artifacts
Importing artifacts by type with a CSV file
CSV import file format
Importing all governance artifacts with a ZIP file
Exporting governance artifacts
Workflows for governance artifacts
Categories
Predefined categories
Designing categories
Managing categories
Managing category collaborators
Category collaborator roles
Creating custom category collaborator roles
Importing or exporting categories
Policies
Designing policies
Governance rules
Designing governance rules
Data protection rules
Designing data protection rules
Filtering rows
Mask data
Data protection rules enforcement
Managing data protection rules
Data quality SLAs
Designing data quality SLAs
Managing data quality SLAs
Business terms
Designing business terms
Predefined business terms
Managing business terms
Authoring business terms
Generating business terms
Creating glossaries with MCP
Classifications
Designing classifications
Predefined classifications
Data classes
Designing data classes
Adding matching methods to data classes
Predefined data classes
Predefined data classes details
Reference data
Designing reference data sets
Creating reference data sets with composite keys
Importing files for reference data sets
Relationships between reference data sets
Predefined reference data sets
Reporting queries
Knowledge Accelerators
Notices
KA for Cross Industry
KA for Energy and Utilities
KA for Financial Services
KA for Healthcare
KA for Insurance
Getting started
Artifacts available to import
Cross Industry
Energy and Utilities
Financial Services
Healthcare
Insurance
Components
Use of governance artifacts
Category areas and subcategories
Business terms
Relationships
Custom attributes
Classifications and tags
Business Core Vocabulary
Subcategories
Concept terms
Property terms
Relationship terms
Business Performance Indicators
Subcategories
Performance analysis terms
Measures
Industry Alignment Vocabularies
Alignment area categories
Alignment topic categories
Alignment terms
Business Scopes
Subcategories
Business Scopes available for separate import
Cross Industry
Energy and Utilities
Financial Services
Healthcare
Insurance
Reference data sets
Data classes
Policies and rules
Synonyms
Using and customizing
Masking watsonx.data assets in watsonx.data intelligence
Resynchronizing assets and artifacts in the knowledge graph
Data lineage
Lineage for unstructured data
Preparing data for data lineage
Viewing data lineage
Managing data lineage graph
Configuring alias assignments
OpenLineage integration
Mapping OpenLineage events
Designing mappings for OpenLineage events
Creating mappings for OpenLineage events
OpenLineage mappings tutorial
Configuring agents for lineage metadata import
Exporting data lineage
Exporting data lineage to Collibra
Configuring Collibra export
Exporting data lineage to OpenLineage format
Designing lineage export
Creating an export asset and managing jobs
Administration
Administration on IBM Cloud
Setting up the platform on IBM Cloud
Setting up the IBM Cloud account
Managing users and access
Adding users to the account
Levels of user access roles
User roles for watsonx.data intelligence on IBM Cloud
Creating custom roles
IAM access groups
Setting up IAM access groups
Example IAM access groups
Setting up Cloud Object Storage
Setting up watsonx.data intelligence
Setting up watsonx.data integration
Creating the Platform assets catalog
Managing the platform on IBM Cloud
Customizing the branding of the web browser
Monitoring account resource usage
Setting up trusted profiles
Managing account settings
Managing all projects in the account
Upgrading services on the platform
Managing Cloud Object Storage resources
Removing users
Stop using services or the platform
Security on IBM Cloud
Network security
Enterprise security
Account security
Data security
Collaborator security
Security policies and responsibilities in IBM Cloud
Securing connections to services with private service endpoints
Configuring firewall access
Firewall access for the platform
Firewall access for IBM Cloud Object Storage
Firewall access for DataStage
Firewall access for Redshift
Firewall access for Spark
Firewall access for StreamSets
Administration on AWS
Setting up the platform on AWS
User roles for watsonx.data intelligence on AWS
Managing the platform on AWS
Security on AWS
Account security on AWS
Data security on AWS
Collaborator security on AWS
Configuring firewall access on AWS
Troubleshooting
Connections
Data Product Hub
Data Refinery
DataStage
IBM Cloud Status
IBM Cloud Object Storage for projects
IBM Knowledge Catalog
Can't provision a second service instance
Solving governance artifacts import problems
Synchronize the data policy service (DPS) category caches
New columns do not appear in preview of a connected asset
StreamSets
Managing the user API key
Managing your settings on IBM Cloud
Managing your settings on AWS
Determining your roles
Activity Tracker Event Routing
Managing your cloud account