BACKGROUND: HomeRuns.com has been greater Boston's award-winning online grocer since 1996. HomeRuns.com allows individuals to grocery shop online through the company's storefront or from a catalog containing over 7,000 grocery store items including fresh meats, produce and dairy. Orders are placed via the Internet, phone or fax with next day delivery.

PLATFORMS: Source system running on ODS and Microsoft SQL Server 6.5. Target system running on NT and Microsoft SQL Server 7.0.

PROBLEM SOLVED: With DataStage from Ardent Software, HomeRuns.com built the technical infrastructure for a life cycle marketing database to track customer retention trends and to report on lapsed accounts. Basic e-commerce customer relationship management (CRM) functionality was provided as well.

STRENGTHS: DataStage's automated workflow environment, reusable components, and packaging and deployment features eased development across the enterprise and improved warehouse reliability. Also, DataStage's ability to capture meta data enables developers to maintain the warehouse. For business analysts and end users, DataStage stores information on data movement and transformation, ultimately giving decision-makers more confidence about their information.

WEAKNESSES: The need for MetaBroker add-ins to perform sophisticated meta data reports or cross-reference meta data between the query tool and data modeling tool repositories has been addressed in the newly released DataStage XE.

SELECTION CRITERIA: Although we evaluated several tools, we opted for transformation engine tools rather than code generators. Several factors ultimately led us to choose DataStage:

  • Performance. DataStage significantly outperformed other products on the market, executing the same routines as fast or much faster than competitors.
  • Functionality. We could extract and transform data from operational systems much easier using DataStage. Additionally, DataStage provided a flexible environment that allowed us to perform data transformations and manipulations either in the source system or in the transformation engine itself without first writing the data into a flat file.
  • Fulfilled Requirements. We needed a tool to build a warehouse ­ this is DataStage's strength. Competing tools did not allow us the freedom to build from different sources. We load data from several data sources every day and the formats change weekly, so flexibility was key in the product choice.

VENDOR SUPPORT : Technical pre- and post-sales support was responsive and well prepared. Technical support was responsive and, when necessary, escalated a technical issue up the chain of command in order to deliver a solution.

DOCUMENTATION: The documentation is online and easy to follow. It has helped me to solve several problems, eliminating the need to call tech support.

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