Data modeling is one of the oldest information management disciplines. However, it experienced a significant shift in recent years and is rapidly expanding. Emergence of dimensional data first shook the foundations of entity-relationship modeling and raised questions about the use of normalization. Today we see new technologies - columnar and correlation databases, for example - driving further change in the modeling of structured data. Beyond structured data we find new challenges in unstructured data - text, images, voice, video, etc. Then there are the specialized data structures that challenge modelers to integrate them with mainstream corporate data - geo-spatial and location-based data, RFID tagging, clickstream and web analytics from e-commerce, and more.
CIMP - Data Modeling specialization builds upon education to certify knowledge and understanding of data modeling techniques and solutions demonstrated by passing several challenging exams. Each exam is aligned with the material in one of the courses in eLearningCurve's Data Modeling curriculum taught by industry leaders, such as David Haertzen, Steve Hoberman, and Rick Sherman.
To obtain CIMP - Data Modeling designation you must pass 5 exams: three required exams covering various fundamental data modeling areas, and two elective exams. You are allowed three attempts to achieve a passing score on each exam. Each attempt, however, will present you with a different set of questions than previous attempts.
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