The layout of data in models, such as tables of historical data, tables of inputs, conversion and indexing factors and how to effectively work with those tables in retrieving data for the use of calculations in forecasts is the topic covered in this module.  At one level, this is a straight-forward requirement, but as models become more complex, many users find they have difficulties and errors creeping in that make the management of the source data difficult and the use of the data in their forecasting formulas becomes challenging.

This module canvasses proven techniques for removing the headaches and demonstrates techniques to simplify the referencing and gathering of data based on input values or key values derived by calculation.  Dealing with multi-value keys, reducing the complexity in lookup and matching calculations to make the model easier to manage and audit is a key focus.  This module is designed to help the user solve real-world problems.