Business-intelligence data-warehouse requirements can be interpreted a lot of ways. We like to take a simple approach whenever possible and champion an architecture that is flexible, scalable, easy to maintain, and, most importantly, easy to use. Don’t just use tools for the sake of using tools; make a solid business case for it. We take great pride in offering creative architecture solutions that are designed specifically around an organization’s data, budget, and capacity to support their architecture after our engagement.

Case Study: Data Warehouse and Business Intelligence Architecture

When considering a technical architecture for your data warehouse and reporting, the platforms, tools, and methodologies can be overwhelming. There are a hundred ways to get what you need, but what is the right way for your organization? The following are high-level examples of successful architectures we have implemented for clients:

  • On-premise MS SQL Server data sources, on-premise MS SQL data warehouse, on-premise SQL Server Reporting Services (SSRS)/Tableau Server Reporting
  • On-premise MS SQL Server data sources, cloud MS SQL data warehouse, cloud Tableau Server Reporting
  • On-premise/cloud data sources with different data source types, hybrid on-premise/cloud data Azure SQL data warehouse, metrics delivery via web API
  • Cloud data sources, multi-region cloud Amazon AWS RDS MS SQL data warehouse, on-premise data analytics using Tableau Desktop and Excel PowerPivot

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