Data Modelling for the Data Lakehouse

A well-designed data model is the foundation of a reliable, scalable, and efficient data warehouse. It determines how data is stored, accessed, and interpreted, ensuring that your analytics environment supports business goals and delivers trustworthy insights.

Data Modeling at NJIT

  • We start with business requirements and ensure we understand the grain at which teh client needs the data.
  • We use consistent naming conventions for tables and fields and ensure we stick to teh guidelines Data Governance has set up.
  • We document relationships, keys, and transformation rules and ensure we explain this to teh client.
  • Regularly review and update the model as business processes change.
  • We use Data Vault modeling patterns to ensure every model being built is scalable.

 

Key Benefits of Data Modeling

  • Consistency: Ensures that data is structured in a uniform way across the organization.
  • Performance: Optimizes queries, reducing load times and compute costs.
  • Clarity: Makes relationships between data elements easier to understand for analysts and stakeholders.
  • Scalability: Allows the warehouse to grow and adapt to new business needs without breaking existing reports.
  • Data Quality: Prevents duplication, enforces standards, and maintains referential integrity.