Frances Villafuerte

  • DB2 Sessions: Room C first floor

    Session Evaluation

    Abstract 

    High demand of large and complex data format has become an essential requirement in today’s business model. DB2 LOB data type enabled the user to process data with various format and maximizing the capability of storing large data. Managing the large volume of data has been a challenging task for DBA. DB2 for z/OS V12 has many enhancements to assists users in managing the LOB table space. This presentation will provide a comprehensive overview of managing Large Data (LOB) and it best practice

    Objective 1:Overview of LOB data type and its operation 

    Objective 2:What affects the performance of LOB table space

    Objective 3:Db2 12 enhancement for performance and data compression 

    Objective 4:Additional tips and hits when operating Db2 utilities with LOB

    Objective 5:Performance recommendation Various techniques in managing the LOB data to reach optimal performance and its best practice

  • DB2 Sessions: Room C first floor

    Session Evaluation

    Abstract 

    Db2 for z/OS strategist Universal Table Space (UTS) has been a widespread adoption by many customers as they have been taking actions to convert legacy table space to UTS. Identifying which type of UTS table space to be used has become a challenge task for DBA. This presentation will provide a lesson learned from customer’s experience and things to think about and its best practice. 

    Objective 1:Overview of design rational of Partition by Growth, Partition by Range or Partition by Range RPN table space.

    Objective 2:This presentation will provide use case of each type of UTS.

    Objective 3: Many table space attributes such as SEGSIZE, DSSIZE, MEMBER CLUSTER or MAXPARTITION can affect the operation of UTS. This presentation will provide information on how table space attributes affect performance on UTS.

    Objective 4: How indirect reference records affects space usage and performance. 

    Objective 5: Recent experience learned from customer - use case