Data modeling has shifted significantly in recent years. This field has expanded rapidly from a stable discipline that concentrated on relational organization of structured data. The arrival of dimensional data resonated throughout the foundations of entity-relationship modeling and brought into question the use of normalization.

Now we as a community are seeing new technologies - columnar and correlation databases, for example - pushing further change in the modeling of structured data. Beyond our structured data, we are faced with new obstacles in unstructured data - text, images, voice, video, etc.

Let's not forget there are the specialized data structures which challenge data modelers to combine them with corporate data - geo-spatial and location-based data, RFID tagging, clickstream and web analytics from e-commerce, and more!

The world of OLTP data has evolved for most data modelers. We have lost the freedom to create optimal databases soley for transaction processing. We seek instead to unravel the obscure data structures of ERP databases and to join those data structures with other various corporate data.

Included is enterprise data modeling, once thought to be too slow, too costly, and of too little value, has been revitalized having found new interest and purpose.

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