Intelligent Enterprise

The dichotomy in the evolution of data modeling tools (described in my previous blog) is of more than historical interest; it goes to the heart of how IT shops manage information modeling and software design. It's also a key differentiator in corporate IT philosophy and approach, with potential impact on capabilities and effectiveness.

Analyst Jeffrey Hammond, co-author of a recent Forrester Research report on the data modeling market, finds that organizations aligned more traditionally -- with clearly delineated database administrator and data modeling/architect roles -- tend to favor classic data modeling tools like CA ERwin. Organizations with an emphasis on integrated enterprise architecture are more likely to favor tools like Sybase PowerDesigner, with its integrated modeling platform that goes beyond data. For organizations looking to empower developers, Hammond recommends tools like Embarcadero ER/Studio and Microsoft Visual Studio.

With recent trends and developments in interrelated areas such as data warehousing, business intelligence, master data management, data integration (e.g. for ERP reporting) and data governance, the future of data modeling tools is beginning to look very different than their past. Organizations need to take a long, hard look at their IT strategy and requirements before committing to any tool (or a tool vendor), Hammond advises. Selecting a data modeling tool begins with closely examining the evolutionary path of the vendor as well as the architectural leanings of the tool, and then determining how that aligns with your IT strategy and goals.

For example:

• Microsoft Entity Data Modeler, part of Microsoft Visual Studio, is well suited for a Microsoft.Net shops that work primarily with Microsoft SQL Server databases and where developers are empowered with data-related responsibilities. It will probably not be the tool of choice for heterogeneous data access requirements or where the data modeling function resides with the data architecture or database administration group.
  
• IT shops that implement custom database standards will benefit from ERwin's customizable templates for forward engineering SQL code in order to, say, generate database tables or views directly from the data model.
  
• Integration between EA/Studio and CodeGear (which Embarcadero acquired last year from Borland) offers potentially interesting options for those looking for closer alignment between process, data and code.
  
• IT shops looking to empower enterprise architecture teams -- and more tightly control modeling and design activities and artifacts -- should look closely at the integrated tools in Sybase PowerDesigner.

Optional capabilities are leading to wider price ranges for data modeling tools, from a few thousand dollars for the base product up to the low five-figure range for full suites. Look for community editions -- free versions of data modeling tools with limited capability -- to test the waters before fully wading in.

As organizations become increasingly data aware and data driven, the ability to understand and define data -- to effectively deploy data for operational efficiency and competitive advantage and as a precursor to data governance -- is becoming increasingly critical. As such, tools that help us understand, define and integrate data will only gain in importance and ubiquity.

Relational data modeling is a very mature science and I am seriously concerned that, left to themselves, vendors will be tempted to invest minimally in enhancing data modeling tools, treating them as cash cows kept on a starvation diet. However, I'm also hopeful that business demands and competitive forces will continue to spur innovation in data modeling.

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