What is Process Asset Library?

Documentation, Process Asset Library, PAL, SOP, Procedures, Artifacts, CMM, CMMI
Documentation

 

What is Process Asset Library (PAL)?

Process Asset Library (PAL) is a centralized repository, within an organization, which contains essential artifacts that document processes or are process assets (e.g. configuration Items and designs) used by an organization, project, team, and/or work group.  The assets may, also, be leveraged to achieve process improvement, which is the intent of lessons learned document, for example.

What is in the Process Asset Library (PAL)?

Process Asset Library (PAL), usually, houses of the following types of artifacts:

  • Organizational policies
  • Process descriptions
  • Procedures
  • Development plans
  • Acquisition plans
  • Quality assurance plans
  • Training materials
  • Process aids (e.g. templates, checklists, job aides and forms)
  • Lessons learned reports

 

Related References

CMMI Institute

What Is Capability Maturity Model Integration (CMMI)?

Building Organizational Capability

 

Data Modeling – Fact Table Effective Practices

Database Table
Database Table

Here are a few guidelines for modeling and designing fact tables.

Fact Table Effective Practices

  • The table naming convention should identify it as a fact table. For example:
    • Suffix Pattern:
      • <<TableName>>_Fact
      • <<TableName>>_F
    • Prefix Pattern:
      • FACT_<TableName>>
      • F_<TableName>>
    • Must contain a temporal dimension surrogate key (e.g. date dimension)
    • Measures should be nullable – this has an impact on aggregate functions (SUM, COUNT, MIN, MAX, and AVG, etc.)
    • Dimension Surrogate keys (srky) should have a foreign key (FK) constraint
    • Do not place the dimension processing in the fact jobs

Related References

Data Modeling – Dimension Table Effective Practices

Database Table
Database Table

I’ve had these notes laying around for a while, so, I thought I consolidate them here.   So, here are few guidelines to ensure the quality of your dimension table structures.

Dimension Table Effective Practices

  • The table naming convention should identify it as a dimension table. For example:
    • Suffix Pattern:
      • <<TableName>>_Dim
      • <<TableName>>_D
    • Prefix Pattern:
      • Dim_<TableName>>
      • D_<TableName>>
  • Have Primary Key (PK) assigned on table surrogate Key
  • Audit fields – Type 1 dimensions should:
    • Have a Created Date timestamp – When the record was initially created
    • have a Last Update Timestamp – When was the record last updated
  • Job Flow: Do not place the dimension processing in the fact jobs.
  • Every Dimension should have a Zero (0), Unknown, row
  • Fields should be ‘NOT NULL’ replacing nulls with a zero (0) numeric and integer type fields or space ( ‘ ‘ ) for Character type files.
  • Keep dimension processing outside of the fact jobs

Related References

InfoSphere DataStage – DataStage Parallel Job Peer Code Review Checklist Template

Peer code review happens during the development phase and focuses on the overall quality and compliance to standards of code and configuration artifacts. However, the hard part of performing a Peer code review isn’t, performing the review, but rather to achieving consistency and thoroughness in the review.   This is where a checklist can contribute significantly, providing a list of things to check and providing a relative weight for the findings.  I hope this template assists with your DataStage job review process.