Using Conceptual Data Modeling to Ensure High Information and Data Quality

Pete Stiglich
Senior Consultant
EWSolutions

Monday 8:30am - 12:00pm

Level: Basic/Introductory

Information and Data Quality are impacted by many factors, not least of which are data models. Unfortunately, it is very common for data modelers, DBAs, or developers to begin the modeling effort at the Logical Data Model level - or even start with a Physical Data Model!!

Instead, to ensure the correct understanding of the topic being modeled and to ensure that Information and Data Quality are built into systems, a Conceptual Data Model (CDM) should be the first model to be developed, reviewed, and approved. Bypassing the CDM phase often leads to assumptions being made that can severely impact Information and Data Quality. For example, missing a “many-to-many” relationship can result in data duplication or missing data. By identifying the business data entities and relationships, a CDM helps identify areas for data reuse, facilitates more accurate design of downstream models, and is a critical enabler of Data Governance. Attendees will learn how to develop Conceptual Data Models to ensure that downstream Logical and Physical models fulfill their critical role in ensuring high information and data quality. Conceptual Models can also support data inventory and taxonomy efforts. This seminar is of interest to business and IT professionals alike.