Data Warehouse & Data Lake Services

In today’s data-driven world, organizations generate massive amounts of structured and unstructured data. To unlock the full value of this information, businesses need the right platforms to store, organize, and analyze data efficiently. Our Data Warehouse & Data Lake Services help you transform raw data into meaningful insights, enabling smarter decisions and future-ready analytics.

Our Approach to Data Modeling

What is a Data Warehouse?

A Data Warehouse (DW) is a centralized repository designed to store structured, historical data from multiple sources. It is optimized for reporting, analytics, and BI dashboards.

Why Data Modeling Matters

• Foundation of Data Warehouse – Defines how data is stored, connected, and retrieved.

• Improved Data Quality – Reduces redundancy, inconsistencies, and errors.

• Performance Optimization – Speeds up queries and reporting.

• Future-Ready Design – Supports scalability as your business grows.

Our Approach to Data Modeling

We follow a proven, step-by-step methodology to ensure models align with both technical requirements and business goals.

1. Requirement Gathering

• Understand business objectives & reporting needs.

• Identify key data sources (ERP, CRM, flat files, APIs, etc.).

• Define KPIs and analytical goals.

2. Conceptual Modeling

• Create high-level Entity-Relationship (ER) diagrams.

• Define business entities, relationships, and rules.

3. Logical Data Modeling

• Build models that define attributes, primary/foreign keys, and normalization levels.

• Ensure consistency across business domains.

4. Physical Data Modeling

• Translate logical models into database structures (tables, indexes, partitions).

• Optimize for performance, scalability, and storage.

5. Implementation & Validation

• Apply models in data warehouse platforms (Snowflake, Redshift, BigQuery, SQL Server, etc.).

• Test for data integrity, query performance, and reporting accuracy.