Data Warehouse 
AWS Redshift 
SQL Server
Performance Tuning
DataStage ETL



Wells Fargo Mortgage, Inc

  • Data Stage development for the Centralized Data Hub project.  The CDH architecture uses Data Stage based on sequential files, and a number of jobs were developed, to offer patterns to other developers to use in the rapid development projects (via Containters).  Verification of primary keys (from a sequential file) was performed via a Sort Stage, adding a key change parameter into the flow, allowing the Copy Stage to split a key failure output as well as a source data output.
  • Data Stage development for the Financial Data Mart, Star Schema project.  Multiple fact tables populated through a number of Data Stage jobs (based on multiple time dimensions).  Numerous data sets and UDB tables joined within the Data Stage Join stage, including a number of Build Op stages to perform transformations.  Resulting fact job populates a 300 column fact table supporting 3.5 million rows.  Dimension tables are built hanging off the fact table and refreshed on a daily basis, again through the use of Data Stage jobs. 
  • Data Stage development for the You Owe Me (YOM) data warehouse project.  Reception of 61 full refresh and 2 incremental daily feeds, flow into 63 data stage jobs which perform business defined transformations through multiple Build Ops stages.
  • Data Stage development for the Timer Database data mart.  This data mart is supports a single fact table with 12 dimension tables.  The fact table is built via the flow of data from a Sequential File stage, outer joining to multiple UDB tables landing into a, daily refreshed fact table.  The 12 dimension tables are refreshed daily as well, via 12 Data Stage jobs. 
  • Data Stage development of 285 daily data feed Customer Survey project.  Use of the Funnel stage to union the common data to 45 unique formats.  Then developed Build Ops stages for each of the 45 to implement business rules.  The 45 tables again are then consolidated into 4 tables, extracted from the enterprise data warehouse and delivered to the business data mart.
  • Data Stage development for multiple projects performing a Multiload Stage to refresh data in the Teradata Active Data Warehouse.  ETL transformation is performed via the Build Op stage, and the Teradata native tables are refreshed on a daily basis.
  • Multiple maintenance projects performed against numerous Data Stage production jobs.  Some efforts include the splitting of the Sequential File stage output to perform round-robin output, writing to each partition, modification of Build Ops stages to strip hexidecimal characters from source data, and more.