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Last Updated Date Mar 10, 2022 |

Challenge

Establishing a robust set of Naming Conventions prior to the start of development is imperative for developing easily maintained data integration mappings and objects.  Naming convention standards should be agreed upon and ready to be implemented at installation time. The longer the delay during development, the more objects are created with no standard that are costly to update later.

Description

The suggestions in this Best Practice focus on the objects and services within the Informatica Cloud Data Integration Platform. Choosing a convention that works for an implementation and then sticking with it is the key to realizing the cost savings to maintenance and development.

The use of good naming conventions facilitates smooth migrations and improves readability by providing a clear understanding of the processes being affected to anyone reviewing or carrying out maintenance in Informatica Cloud Data Integration. If consistent names and descriptions are not used, more time may be needed to identify all of the objects and services and their intended usage and stakeholders. When determining naming standards, keep possible and likely future environment changes in mind so that the names will not become confusing later on. You may be developing for a single application to start but consider when you have multiple applications. Ensure all naming standards are prepared for growth.

The table below offers suggested naming conventions for various Informatica Cloud Data Integration objects. Whichever convention is chosen, the selection should be made very early before installation (while reviewing the installation documentation) and development cycles and published broadly across all developers, testers, and system support personnel. A process to adhere to standards is recommended to ensure that all developers follow and adhere to the guidelines. These are easy to enforce as objects are created, but costly to fix and retest later.

Asset Type

Convention

Example

ICDI Connection

conn_[Connection Type]_[application name]_[optional logical name]_[schema name]

conn_orcl_newapp_dnb_contact

conn_restv2_oldapp_get_contacts

ICAI Connection

[Connection Type]-[application name]-[optional logical name]-[schema name]-Conn

sfdc-oldapp-communities-Conn

ICDI Data sync task

dss_[source]_[optional_source_domain]_[target]_[target domain]_[action]

dss_wd_orcl_workers_insert

dss_orcl_cih_ciholdap_subscribe

ICDI Data Replication Task

drs_[source]_[source domain]_[location]_[target]

drs_sfdc_sales_backup_ff

drs_orcl_hr_snowflake_db

ICDI Mapping task

mct_ [source]_[source_domain]_[target]_[target domian]_[action]

mct_wd_apac_salesgroup_orcl_dw_insert

CIH Subscription

SUB_[optional application]_[optional topic]_[data task target details]

SUB_oldapp_sales_orcl_dw_emp_insert

ICDI input parameter

[param type]_[optional related transform]_[optional source]_[fieldname]

CamelCasing

pdo_tgt_orcl_dbname

BatchTaskId

LastRuntime

Naming Conventions

Environment General Recommendations

Environment Lifecycle Abbreviations

Abbreviations

Description

Native Account Name

DEV, DV

Development

     user@example.com.dev

TST, ST, QA

Testing, System Test, Quality Assurance

     user@example.com.qa

UAT, UT

User Acceptance Testing

     user@example.com.uat

PRE,PREVIEW

IICS Preview Environment

     user@example.com.preview

BC,BCK,STANDBY,PRD_ALT

Business Continuity Environment

     user@example.com.bc

PD, PRD, PROD

Production

     user@example.com.prod

Cloud Naming Conventions

Secure Agent

Secure Agent

Abbreviation

Naming Convention

Example

Description

Secure Agent

SA

SA_[ENVIRONMENT]_ [ECOSYSTEM]_[SERVER]

SA_Azure_ Wndws01

The secure agent is the executable that runs the integrations on the designated server.

Secure Agent Group

SAG

SAG_[ENVIRONMENT/REGION]_ [CAPACITY]_[ECOSYSTEM] _[SERVER SET]

SAG_AWS_CIH Linux02

The secure agent group logically bands the executables that runs the integrations on their respected designated servers.

Repository Objects

Many decisions in the conventions below are based on a familiarity with Informatica PowerCenter. These include:

  • prefixing with abbreviations
  • the use of underscores
  • alphanumeric sorting of project and folder for intentional default ordering

Repository Object

Abbreviation

Naming Convention

Example

Description

TaskFlow

tf/TF

tf_[optional single target]_[Goal]

tf_EDW_ Dimensions_Load

The TaskFlow is ICDI composite job, representing a set of tasks. TaskFlow Name should identify the end goal – i.e., Calendar Dimension load or Dimension Table load

Linear tasks and advanced tasks should share this naming

Mapping Task/Mapping Configuration Task

Mct/MCT

mct_[optional task]_[source]
_[source_domain]
_[target]_[target domian]_[action]

MCT_INTV03_SDFC
_ACCOUNT_EDW
_SFDC_ACNT _INSERT

MCT_INTV04_SDFC
_ACCOUNT_CRM
_SFDC_ACNT _INSERT

mct_wd_workers_non
_active_corphr
_legal_update

A Task is term for one of many functional ETL jobs. A Mapping task is one task type, retaining all environment and design metadata sufficient to execute.  The name pattern here conveys, in English: [task] to [action] records to the [target_domain] in the [target] from the [source_domain] in the [source]

Mapping

M/m

m_[source details]_[target details]

M_SFDC_ACCOUNT
_SFDC_ACNT_INSERT

m_wd_workers
_corphr_workers

The Mapping is the Design document, leveraging a pattern of connected data transformations.

Omitting the task details, a mapping still mirrors its intended task

Data Synchronization/Data Replication

DSS

DRS

dss__[optional task]_[source]_[source_domain]
_[target]_[target domian]_[action]

drs_[source]_[source_domain]
_[target details]

dss_wd_orcl_workers_insert

drs_orcl_hr_snowflake_db

ICDI tasks for ETL synchronization and replication.

As tasks, they should mirror all task naming conventions

Database Mass Ingestion/File Mass Ingestions

DBMI

FMI

MI

dbmi_[source]_[source_domain]
_[target details]

fmi_[source]_[source_domain]
_[target details]

dbmi_orcl_franchise_ads
_DailyODSSnapshot

fmi_SFTP_VendorV2
_LoadTenderRejected

mi_emrsys_inr_intake
_int289

Mass Ingestion provides tasks for file, streaming and DB.  A shared mi_ prefix could be used

Cloud Integration Subscription/Publication

PUB_

SUB_

pub_[optional application]_[source]_[topic details]

sub_[ optional application]_[topic]_[target]

pub_ieast_securitylog
_unifiedlogRaw

sub_mediaTrends
_jupyter_landing

Data Integration tasks (mappings and syncronizations) used with CIH should have _PUB_ and _SUB_ added to their names, respectively

Cloud Application Service Connectors

SvcConn

[system or site]-[optional endpoint name]-[action set]-SvcConn

IICS-RESTAPI-V2Admin
-SvcConn

NOTE:

-    ICAI assets use hyphens in place of underscores

-    Application Integration Suffix naming conventions apply a naming distinction from Data integration prefixing

Cloud Application Process Objects

PO

[optional type or group]-[objectName]-[optional list identifier]-PO

PurchaseOrderItems
-List-PO

wdr-worker-PO

Note that PO object names do not show in schema when referenced, given a name during schema creation

Project

N/A

None

CRM_NextGen

CIH_Subscriptions

Default

Z_DEV_jsmith

zz_proof_of_
concept_stuff

1_flow_project

2_flow_project

 

 

The Project is the highest level in IICS organization hierarchy. It contains assets and folders. Asset grouping should be project based.  As project/folder hierarchy is used in export/import, shared assets should be shared in their own project.

The ‘Default’ project is always present.  If projects should be deemed required to have individual owners, project name should identify owner.

Folder

N/A

Per asset (Mappings, Tasks, …)

Per task (sales,hr,shared)

Per integration type(Batch, Process,Hub)

 

The Folder is the second highest level in your asset organization hierarchy. It should be used to logically group assets. The grouping can be based on project requirements, which compliments a ‘Per asset’ folder naming.

Connection Prefixing

Conventions below are for use in prefixing Data Integration connections based on connector type but are not exhaustive of all connections. Other connection tips include:

  • A maximum length for connection names of 100 characters
  • Avoid identifying any environment (DEV, SIT, PROD) but it’s okay to identify by region (EAST, APAC) or version (v1, bigsur).
  • Application Integration ICAI connection should omit the underscore as it is not permitted.
  • For support of Cloud Integration Hub, environments are required to have a single CIH connector type, named “Cloud Integration Hub”.

Connector Name

Naming Convention

Category

Subcategory

PostgreSQL

conn_psql_

Cloud

Database

MySQL

conn_mysql_

Cloud

Database

Amazon RDS MySQL (Community)

conn_rds_

Cloud

Database

Amazon RDS Oracle

conn_rds[optional _orcl]

Cloud

Database

Amazon RedShift, and  V2

conn_redshift_

Cloud

Data Warehousing

Amazon S3

conn_S3_

Cloud

Storage

Amazon S3 V2

conn_S3v2_

Cloud

Storage

Hadoop Files V2 (Complex File)

conn_hdfs_

Tech

Files/ Documents

Hive Connector

conn_hive_

Tech

Files/ Documents

KAFKA (Near realtime/Microbatch)

conn_kafka_

Tech

Streaming

AS2

conn_as2_

Tech

Files/ Documents

Atlassian Jira, Jira Cloud

conn_jira_

Application

Project Management

Coupa V2

conn_coupaV2

Application

Financials

Cvent

conn_cvent

Application

Marketing Events

File I/O

conn_fileio_

Tech

Files/ Documents

Flat File

conn_ff_

Tech

Files/ Documents

FTP/sFTP

conn_sftp_

Tech

Files/ Documents

Google Analytics

conn_

Cloud

Analytics

Google BigQuery

conn_gcp_bqv2

Cloud

Database

Google BigQuery V2

conn_gcp_bqv2

Cloud

Database

Google Cloud Storage, V2

conn_gcp_storage

Cloud

Storage

ODBC Generic

conn_odbc

Cloud

Data Warehouse

DB2 Warehouse on Cloud

conn_db2_[cloud]_

Cloud

Data Warehouse

IBM Netezza

conn_netezza_

Tech

DW

JDBC_IC

conn_jdbc_

Tech

Database

JSON  Target

conn_json_

Tech

Data Format

LDAP

conn_ldap

Tech

Directory Access

Marketo V3

conn_marketo_

Application

Marketing Automation

Microsoft Azure Blob Storage V3

conn_adls_blob_

Cloud

Storage

Microsoft Azure Cosmos DB SQL API

conn_cosmosdb

Cloud

Files/ Documents

Microsoft Azure Data Lake Store V3

conn_adls_

Cloud

Data Lake

Microsoft Azure Data Lake Store Gen2

conn_adls_gen2_

Cloud

Data Lake

Microsoft SQL Server

conn_[azure_]mssql_

Cloud

Database

Microsoft Azure SQL DW V3

conn_[azure_]dw_

Cloud

Data Warehousing

Microsoft Dynamics 365 Operations

conn_mscrm_ops_

Application

ERP

Microsoft Dynamics 365 Sales

conn_mscrm_

Application

CRM

Microsoft Excel v2 (via ISD)

conn_msexcel_

Tech

Database

Microsoft SharePoint Online

conn_mssharepoint_

Application

Collaboration

Microsoft SQL Server

conn_mssql_

Tech

Database

Oracle DB

conn_orcl

Tech

Database

Oracle Eloqua BULK

conn_elq_blk

Application

Marketing Automation

Oracle Eloqua REST

conn_Elq_REST

Application

Marketing Automation

Oracle JD Edwards EnterpriseOne

conn_jde_

Application

ERP

NetSuite

conn_netsuite

Application

ERP

Qlik

conn_qlik

Tech

Analytics

Salesforce Analytics

conn_sfdc_

Application

Analytics

Salesforce Marketing Cloud

conn_sfdc_mc_

Application

Marketing Automation

SAP - BAPI/ RFC (Mapplet)

conn_sap_babi

Application

ERP

SAP -Table Reader / Writer

conn_sap_

Application

ERP

SAP IDOC

conn_sap_idoc_

Application

ERP

SAP Concur V2

conn_concur

Application

Travel and Expense

ODBC (with HANA as sub-type)

conn_SAPHanaDbCldODBC

Tech

Database

ODBC (with HANA as sub-type)

conn_SAPHanaDWCldODBC

Tech

Data Warehouse

ODBC (with HANA as sub-type)

conn_SAPHanaDbODBC

Tech

DW

SAP SuccessFactors OData

conn_SAPScsFctrOdata

Application

HCM

SAP SuccessFactors LMS

conn_SAPScsFctrLMS

Application

HCM

Snowflake Cloud Data Warehouse V2

conn_sf_

Cloud

Data Warehousing

Tableau

conn_tbu_

Tech

Analytics

Teradata Bulk (TPT)

conn_terad_bulk

Tech

DW

Salesforce

Conn_sfdc_

Application

Life Sciences

REST V2

conn_restv2_

Tech

Webservices

WS Consumer

conn_ws_

Tech

Webservices

Xactly

conn_xctly

Application

Incentive, Compensation

XML source/ target

conn_xml

Tech

Files/ Documents

Zendesk V2

conn_zendesk_

Application

CRM

Zuora Aqua

conn_zuora_aqua

Application

Commerce/ Billing

Transformation Naming Conventions 

Naming Convention

Example

Application

Description

[SRC_[CONNECTOR] _[OBJECT]

Src_Orcl_Accounts

Data Integration

Reads data from a source.

[TGT_[CONNECTOR] _[OBJECT]

Tgt_AWS_Customer

Data Integration

Writes data to a target.

[Agg_[CONNECTOR] _[OBJECT]

Agg_SalesOrders_ FactSalesTransaction

Data Integration

An active transformation that performs aggregate calculations on groups of data.

[Cln_[CONNECTOR] _[OBJECT]

Cln_Phonenumbers_ DimCustomer

Data Quality

A passive transformation that adds a cleanse asset that you created in Data Quality to a mapping. Use a cleanse asset to standardize the form and content of your data.

[Msk_[CONNECTOR]_[OBJECT]

Msk_SSN_DimPatient

Data Integration

A passive transformation that masks sensitive data as realistic test data for nonproduction environments.

[Ddp_[CONNECTOR]_[OBJECT]

Ddp_Account_ID

Data Quality

An active transformation that adds a deduplicate asset that you created in Data Quality to a mapping. Use a deduplicate asset to find instances of duplicate identities in a data set and optionally to consolidate the duplicates into a single record.

[Exp_[CONNECTOR]_[OBJECT]

Exp_AuditFields

Data Integration

A passive transformation that performs calculations on individual rows of data.

[Ftr_[CONNECTOR]_[OBJECT]

Flt_Error_Accounts

Data Integration

An active transformation that filters data from the data flow.

[HS_[CONNECTOR]_[OBJECT]

HBd_Sales_Territory

Data Integration

An active transformation that converts relational input into hierarchical output.

[HP_[CONNECTOR]_[OBJECT]

HPs_XML_Surveys

Data Integration

A passive transformation that converts hierarchical input into relational output.

[HP_[CONNECTOR]_[OBJECT]

HPc_JSON_PharmacyOrders

Data Integration

An active transformation that converts hierarchical input into relational output.

[Java_[CONNECTOR]_[OBJECT]

Jva_Python_Policy

Data Integration

Executes user logic coded in Java. Can be active or passive based on the Java code.

[Jnr_[CONNECTOR]_[OBJECT]

Jnr_Claim_HdrDtl

Data Integration

An active transformation that joins data from two sources.

[Lkp_[CONNECTOR]_[OBJECT]

Lkp_DIM_PRODUCT_FK

Data Integration

Looks up data from a lookup object. Defines the lookup object and lookup connection. Also defines the lookup condition and the return values. A passive lookup transformation returns one row. An active lookup transformation returns more than one row. Can be active or passive based on the transformation logic in the mapplet.

[Mplt_[CONNECTOR]_[OBJECT]

Mplt_Cleanse_Zip

Data Integration

Inserts a mapplet into a mapping or another mapplet. A mapplet contains transformation logic that you can create and use to transform data before it is loaded into the target.

[Nrm_[CONNECTOR]_[OBJECT]

Nrm_Expense_Categories

Data Integration

Processes data with multiple-occurring fields and returns a row for each instance of the multiple-occurring data.

[Prs_[CONNECTOR]_[OBJECT]

Prs_XML_Customer

Data Quality

A passive transformation that adds a parse asset that you created in Data Quality to a mapping. Use a parse asset to parse the words or strings in an input field into one or more discrete output fields based on the types of information that the words or strings contain.

[Rnk_[CONNECTOR]_[OBJECT]

Rnk_Top_Accounts

Data Integration

An active transformation that limits records to a top or bottom range.

[Rtr_[CONNECTOR]_[OBJECT]

Rtr_Dupe_Orders

Data Integration

An active transformation that you can use to apply a condition to incoming data.

[Rsp_[CONNECTOR]_[OBJECT]

Rsp_Standard_ PhoneNumber

Data Quality

A passive transformation that adds a rule specification asset that you created in Data Quality to a mapping. Use a rule specification asset to apply the data requirements of a business rule to a data set.

[seq_[CONNECTOR]_[OBJECT]

seq_DIM_ CUSTOMER_PK

Data Integration

A passive transformation that generates a sequence of values.

[Srt_[CONNECTOR]_[OBJECT]

srt_Customer_ Income

Data Integration

A passive transformation that sorts data in ascending or descending order, according to a specified sort condition.

[Sql_[CONNECTOR]_[OBJECT]

Sql_Azure_ StoredProc

Data Integration

Calls a stored procedure or function or executes a query against a database. Passive when it calls a stored procedure or function. Can be active or passive when it processes a query.

[UNION_[CONNECTOR]_[OBJECT]

Unn_All_Clients

Data Integration

An active transformation that merges data from multiple input groups into a single output group.

[Vrf_[CONNECTOR]_[OBJECT]

Vrf_Valid_ Address

Data Quality

A passive transformation that adds a verifier asset that you created in Data Quality to a mapping. Use a verifier asset to verify and enhance postal address data.

Data Integration Fields and Parameter Prefixing

bbreviation

Naming Convention

Example

Used for

out

out_[fieldname]

out_lastname

Expression output fields

var

var_[fieldname]

var_ISVALID

Expression variable field

param

param_[fieldname]

Param_s3_source

Input parameter simple type

io

io_[fieldname]

io_bad_row_count

io_run_rowID_max

Input/output parameter fields

pdo

pdo_[data object]

pdo_sfdc_account

Data Object Parameter

i/o

i_[input field name]

o_[output field name]

i_countryname

o_countrycode

For mapplets, input and output fields.

Application Integration Field name

Abbreviation

Naming Convention

Example

Description

in

in_[fieldname]

in_optyID

Input fields

out

out_[fieldname]

out_filerunid

Output fields

sc

sc_[optional in/out]_[fieldname]

sc_out_errorcode

sc_out_result_row_count

Service connector action output fields

var

sys

var_[fieldname]_[optional list identifer]

sys_default_out

var_custdetails

var_reportprocessed_List

Variable fields.

sys_default_out is mentioned here for use as an field target for expressions without resulting values needed

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