We can talk about the features and functionalities of them for days, but at a high level, there are four major differences:
Speed: How fast can we get up and running with the system, answer questions, design and share dashboards, and then change them? This is where systems like Tableau and GoodData are far better than the old-school Business Intelligence tools like BusinessObjects or Cognos. Traditional systems took months or years to implement, with costs running to millions. Tableau has a free trial version that gets installed in minutes, and GoodData is cloud-based, so they are faster to implement by orders of magnitude. They are also faster in giving results: traditional BI requires IT and developers to make any changes to reports, so business users are mostly stuck in a queue waiting to get anything done. Tableau and GoodData provide more of a self-service experience.
Analysis: This is where Tableau excels. It has a powerful and flexible drag-and-drop visualization engine based on some technology from Stanford. GoodData and traditional BI tools typically provide some canned reports but changing them requires significant time and money.
Data layer: This is where the three options are the most different:
GoodData requires us to move our data to its cloud. Traditional BI typically requires us to move our data to its data warehouse. On the other hand, Tableau connects to a variety of existing data sources and also provides a fast in-memory data engine, essentially a local database. Since most enterprises have their data stored all over the place, this provides the most convenient choice and lets companies use the investment they’ve already made.
Enterprise readiness: Traditional BI and Tableau do well here, with enterprise-level security and high scalability.
Related Article: Aggregating Disparate Data Sources At A Large University In Tableau
