Intro to Data ModelingTypes of Data Models
- Best practices for data modelingMichael discusses current best practices for data modeling, which he defines as the process of designing data tables for use by users, BI tools, and applications. 4 considerations to keep in mind when modeling data are: Grain, Naming, Materialization, and Permissioning and governance.
- Notes on data modeling from Handbook of Relational Database DesignWill shares some notes from reading the first half of Handbook of Relational Database Design. He reviews the three-schema approach, properties of an effective data model, taking a data-driven approach towards modeling data, and essential vocabulary.
Common Data Modeling Challenges
These are common challenges people face when gaining expertise in data modeling. Tackling these challenges head-on can help you learn this skill quicker.I'm a senior software engineer working on a project that requires integrating data from multiple sources. Each data source has its own schema and data format, so I'm facing difficulties in mapping and transforming the data to fit into a cohesive structure. How can I design a data model that accommodates the diverse data sources and ensures data integrity and consistency?I'm a software engineer working on designing a data model for a new application. I'm having a hard time determining the optimal structure and relationships between the different entities in the system. I'm unsure how to strike a balance between normalization and denormalization, and I'm concerned about the performance implications of what I decide. How can I ensure that my data model is efficient, scalable, and meets the application requirements?Add your own to track your progress and inspire others
MigrationsConceptual Data Model