Data Services Best Practices Code Naming Conventions

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Code Naming Conventions

The Data Services objects should be named to make it as easy as possible to identify their function and object type. The following table contains the available objects in Data Services and their proposed naming convention.

Object	Naming Convention
Project	PJ<Project Subject Area>_Batch
Job (Batch/Real-time)	JB_<RICEFID>_<name>
Work Flow	WF_<RICEFID>_<name>
Data Flow	DF_<RICEFID>_<SubjectArea Segment>_<Action>
Annotation	ANN_<RICEFID>_description
Catch	CATCH_<RICEFID>_description
Conditional	COND_<RICEFID>_description
Datastore	DS_<SOURCETYPE._<SOURCENAME>
Document	DOC_<RICEFID>_description
DTD (Document Type Definition)	DTD_<RICEFID>_description
File Format	FF_<RICEFID>_<ACTION>_DESCRIPTION
Function	FUNC_<description>
Script	SC_<RICEFID>_description
Template Table	TT_<RICEFID>_description
Try	TRY__<RICEFID>_description
While Loop	While_description
XML Message	XMLMSG_<RICEFID>_description
XML Schema	XMLSCH_<RICEFID>_description
XML Template	XMLTMPL_<RICEFID>_description
Address_Enhancement Transform	AE_<RICEFID>_description
Case Transform	Case_description
Date_Generation Transform	DG_<RICEFID>_description
Effective_Date Transform	ED_<RICEFID>_description
Hierarchy_Flattening Transform	HF_<RICEFID>_description
History_Preserving Transform	HP_<RICEFID>_description
Key_Generation Transform	KG_<RICEFID>_description
Map_CDC_Operation Transform	MC_<RICEFID>_description
Map_Operation Transform	MO_<RICEFID>_description
Match_Merge	MM_<RICEFID>_description
Merge	MER_<RICEFID>_description
Name_Parsing	NP_<RICEFID>_description
Pivot	PIV__<RICEFID>_description
Reverse Pivot	RPIV_<RICEFID>_description
Query	QRY_<RICEFID>_description
Row_Generation	RG_<RICEFID>_description
SQL	SQL_<RICEFID>_description
Table_Comparison	TC_<RICEFID>_description

Other Naming Standards

The naming standards for other components which may be involved in the BOBJ DS process are below.

• Global Variables should be named with a prefix of “$GV_”.
• Local Variables should be named with a prefix of “$V_”

Project

Format:  PJ_<Project Subject Area>_Batch

Example: PJ_PANGAEA-PHASE1-CONV_BATCH

Projects are the highest level of reusable object in Data Services.  They allow you to group jobs that have dependent schedules or belong to the same application.  DESCRIPTION is the general application. PJ is an abbreviation for Project. Batch suffix signifies that all ETL jobs in this conversion project execute in BATCH mode.

Job

Format: JB_<RICEFID>_TARGETSCHEMANAME

Example: JB_CV50001_SALES_LOAD

A job is a group of objects that you can schedule and execute together.  Multiple jobs can be included in a single project.  When naming a job, include a description of data managed within the job.  In the example above, the job loads sales data to a data mart.  JB is an abbreviation for Job.  When designing jobs, you may want to limit the scope of the job to a particular area of your business, so that you can easily understand the purpose of the job from the name.  Keeping the jobs limited in space also makes it easier to re-use the jobs in other projects.

Datastore

Format: DS_<SOURCETYPE._<SOURCENAME>

Example:  DS_SAP_VR2

A Datastore provides connection information for a source or target database.  Data Services is able to import metadata through the data store connection.  The SOURCETYPE could SAP, TD for Teradata, ORCL for ORACLE and so on. SOURCENAME could be the schema name of the database or just a descriptive name for the source or target database.  DS stands for datastore.

Workflow

Format: WF_<RICEFID>_TARGETTABLE

Example: WF_CV50002_SALES_DIM

               WF_CV50007_CUSTOMER

Workflows can contain other workflows are well as dataflows.  TARGETTABLE refers to the final table in the workflow that is being loaded.  In instances where a workflow contains multiple workflows, it can refer to a category or group of tables.  In the examples, WF_CV50002_SALES_DIM hold all the dimension table loads for the SALES data mart application.  One of the workflows is the WF_CV50007_CUSTOMER, which loads only customer data.  WF stands for workflow.

Dataflow

Format: DF_<RICEFID>__<SubjectArea Segment>_<Action>

Example: DF_CV50007_CUSTOMER_EXTRACTFILE

               DF_CV50007_CUSTOMER_TRANSFORM

               DF_CV50007_CUSTOMER_OUTPUTFILE

Dataflows are the lowest granularity objects in Data Services.  Multiple dataflows can reside in a workflow.  Dataflows hold the specific query or transformation that is being applied to the source data.  TARGETTABLE refers to the specific table that the dataflow is loading.  DF stands for dataflow.  In the example, the Customer table data is extracted from file, data is transformed in the 2^nd Data flow. In the 3^rd Data flow, Customer Ouput File is generated for further processing.

Scripts

Format: SC_<RICEFID>__DESCRIPTION

Example: SC_CV50007_CLEANUP_TEMP_TABLES

Scripts can be created in Jobs or Workflows.  They are singe-use objects and are not stored in the Data Services object library. They can be used to declare and assign variables, call a SQL function or perform SQL statements.  DESCRIPTION can refer to the function or task that the script is performing or the name of a table that the script is loading.  SC stands for script.  Note: Dscriptive Names could include (SQL update table X, Print Message, etc.)  This example describes a script that truncates the temp tables for the job.

Flat Files

Format: FF_<RICEFID>_<ACTION>_DESCRIPTION

Example: FF_CV50009_OUT_ORA_APPS_SALES_DETAIL

Flat files are data sources that are not in database table form.  They are typically used in dataflows to create tables or as a source of metadata.  The example describes the target table that the file will populate from the Oracle application.  FF stands for flat file.

Tables

Format:  DESCRIPTION

Example:  KNA1

Tables can be used as a source or target in a dataflow.  DESCRIPTION refers to the data content in table.  The example describes the database table that will house CUSTOMER data.