Data into Information

The process of concentrating high-volume data into information is the application of information engineering, using techniques developed from a variety of disciplines.  These include:

Data Warehouse schemas

Usually from the Management Information Systems (MIS) discipline, schemas are approaches to how databases are structured. MIRG researchers have implemented both the Star, Snowflake, and Constellation of Stars schemas.

Extract Transform Load (ETL) programming

This is a programming step, using a combination of Sequential Querying Language (SQL) and database management software, where data is copied into staging tables, transformed to allow integrated data, then loaded into a data warehouse.  MIRG has undertaken research into highly complex transformations using SQL code and stored procedures (complex code scripts).

Business Process Mapping

Usually taught in management (when taking MBAs), business process mapping is required to design the data warehouse to answer most questions that a user may ask from a business process viewpoint.  MIRG researchers develop business process maps in all projects.

Data Warehouse Design

Also part of the MIS discipline, Entity Relationships (ER) diagrams, Metadata documentation, and data characterization are all required steps in developing a DW, and MIRG researchers get significant experience in this area.  

You are looking at the Data to Information process of the overall flow: