Gain valuable insights from your data with Tableau for NetSuite

At Cadran Analytics they often get the question why you should install a system like Tableau next to a comprehensive system like NetSuite – which contains ERP, CRM, and many other functionalities. Colleague Jelle Huisman – Founder & Data Scientist at Cadran Analytics explains the answer in his blog “Tableau for NetSuite” in four parts: legacy data, external data, performance, and advanced analytics.

Legacy data

When you have just implemented NetSuite, there is very little historical data in the system. For example, it will not be possible to compare sales figures to the previous year. Tableau – in combination with Cadran’s data model for NetSuite – makes it possible to combine data from legacy systems with NetSuite data. This makes the process easier and less time-consuming, and makes it possible to recognize historical patterns.

External data

In addition to data from legacy systems, Tableau can be used to connect to data from other systems. For example, NetSuite CRM contains information about leads and prospects. If you combine data from NetSuite, Google Analytics and a separate API, this can, for example, provide insight into which lead needs attention in which way. These are very helpful insights for the marketing department!


In NetSuite you have the option to easily create ad-hoc reports. This can be practical because this way you have real-time insights from your NetSuite data. But if you create many large of these saved searches, this can negatively impact NetSuite performance. In Tableau the loading time for such reports is short and the data can be refreshed at regular intervals. Therefore, working with Tableau for such reports prevents performance issues in NetSuite.

Advanced analytics

By integrating programming languages such as R and Python into Tableau, advanced methods like machine learning become available. For example, by using relevant historical data, it can predict when to perform maintenance on a machine. This is called predictive maintenance. Another example is analyzing customer churn: by analyzing customer data you can see which customers you might lose if no action is taken. If you intervene at the right time, these customers might be retained.

How this process exactly works and other examples of the benefits of Tableau for NetSuite can be read in the full article on