County Fair, one of South Africa`s largest poultry producers and the largest poultry producer in the Western Cape, has initiated a number of IT-optimisation projects combining its data warehouse, financial and distribution systems to improve its service delivery, asset tracking and production functions.
With its broad operation - from live bird rearing to poultry and protein production - and its distribution across nine provinces, County Fair has developed a sophisticated IT infrastructure incorporating distribution, data processing, account management, customer management and farming systems, all of which have to be co-ordinated for central management.
Ian Stuart, IT consultant to County Fair and director of Stuart Software Consulting, says the projects primarily support the company`s comprehensive order tracking and data collection system used to control the production and distribution of its various products to customers.
"Our challenge was to consolidate data from different sources and keep it consistent for accurate analysis and projection," says Stuart. "County Fair keeps its own sales database which must be consolidated with databases from distributors and customers."
"Using an IBM RS/6000 platform running AIX Unix, and a Universe database, our first project involved building up an extensive sales database with smaller data marts, creating multiple databases from a consistent data source with multiple dimensions (such as customer details, geographical distribution, and so on)," he continues. "This would enable County Fair to accurately produce year-on-year and week-on-week comparisons of its national operation, and keep track of its daily sales process for accurate forecasts."
Central to the project was the extraction, translation and loading (ETL) process, using Ardent`s DataStage, to combine the various data sources into a unified, coherent database to populate the central data warehouse.
"Without DataStage it would be almost impossible to initiate the ETL process within time and budget constraints," says Stuart. "Because DataStage is so well integrated with Universe and takes an easy-to-use visual approach to development, we could see exactly what we were working with and test our transformations with minimal downtime."
Stuart says DataStage`s powerful aggregation features were useful in standardising data formats, important when working with data from multiple sources or with historical data that doesn`t match current reference tables.
"A good example of this is the political changeover from four to nine provinces," he says. "Data referenced on the older political map had to be consolidated in the new database with the new political map as a reference, so data tables had to quickly be translated and adapted."
"With DataStage this was a standard process that was scheduled to run in a controlled environment," he continues. "With built-in exception handling features, any errors in the transformation were automatically logged and manually rectified."
Next in line is a project designed to extract data from reporting and management systems using the consolidated financial system, and build up a performance database for multiple farming operations.
"DataStage will again be used to consolidate the data from the farming operations in the scope of the project, taking into account performance variables from feed type to seasonal variations," says Stuart. "We`re confident the experience we`ve gained so far, combined with the versatility of the ETL process, will help us meet our targets and promote future growth for the company in its market."
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