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The Data Model Scorecard Steve Hoberman is a presenter, consultant, and the author of seven books on data modeling, including the bestseller Data Modeling Made Simple. One of Steve's frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. Steve has just published the Data Model Scorecard book, which helps data professionals apply a scoring standard against their data models in order to assess their quality. This scoring tool contains ten categories aimed at impr...
The Evolution of Data Modeling - by Ron Huizenga When we review the evolution of new data architecture and development methodologies, along with the corresponding changes in corporate culture, we can see that there have been numerous approaches over the years. In the earlier days of traditional / waterfall processes for data modeling, there was a more rigid organizational structure with data modelers, programmers, and system analysts. Agile methodologies emerged in an attempt to address the shortcomings of traditional practices. The focus chan...
The Challenge of Master Data Modeling - by David Loshin I had a recent email exchange in which a customer was looking for guidance in developing data models for master data entities used across multiple business functions and domains. One of the motivating factors was the desire for evolving a “golden record” (a term that makes me bristle each time I hear it, by the way) for each master entity type – a golden customer record, a golden product record, etc. I expressed my concern about two things: attempting to create a model intended to represent a s...
SSWUGtv interview: Ron Huizenga on Data Architecture Challenges Ron Huizenga, ER/Studio Product Manager, gave an interview on SSWUGtv to discuss data architecture challenges that impact us all as data professionals. These key challenges include: New methodologies Big data Multiple diverse data sources Data quality Business focus on usage of the data With many different variables and moving parts, today’s data environments required a dedicated process to manage them effectively. The best approach is still to define a design up front to ensure you ha...
Embrace the Future of Data Architecture: Make the Switch to ER/Studio Sometimes you need to face the inevitable: the tool selected years ago is not the one you need for the future. Have you been struggling with complicated modeling tasks or outdated tools? Are your data models getting too big to handle? We’ve heard from a lot of customers recently who have been frustrated with their old data modeling tools, for multiple reasons such as: Lack of functionality Lack of support Lack of a future roadmap Embarcadero is committed to enabling our users to adapt to...
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