Decision Support
Decision Support Systems (DSS) are computer systems that enable organizations to analyze vast amounts of data obtained from different sources within the organizations. Typical determinations are monthly sales figures of a current period compared to previous periods, projected revenue numbers, simulations of price change effects on sales and inventory related data. They aid organizations in making sound business decisions.

A typical DSS implements the following functions:
  1. Extracting data from a variety of sources, transforming it, and ultimately loading it into the DSS. This process is often referred to as Extraction Transformation and Load (ETL). ETL occurs periodically to synchronize DSS with their data sources.
  2. Loading large amount of already extracted and transformed data. Occasionally it is necessary to reload an entire DSS, e.g., for migration purposes.
  3. Solving problems by sifting through massive amounts of data while applying complex algorithms. Some algorithms are run periodically, e.g., every hour, day, week, or month. This class of algorithm is also referred to as periodic reporting. Some algorithms are developed on the fly by data analysts. This class of algorithms are also referred to as ad-hoc reporting. Many of the ad-hoc algorithms are later run periodically.

The TPC has developed three DSS benchmarks, TPC-H, TPC-DS and TPC-DI. All are designed as enterprise class benchmarks. While they cover all three DSS functions, each focus on particular aspects of a typical DSS. TPC-H focuses on ad-hoc reporting, TPC-DS includes elements of ad-hoc reporting and periodic reporting and TPC-DI focuses on the ETL part of DSS.