Parameter actions are a fairly new feature from Tableau 2019.2 and they are incredibly useful! They can be used in several ways. This article demonstrates how they can be used to switch between data sources.

Snowflake is a unique integrated data platform, conceived from the ground up for the cloud. Its patented multi-cluster, shared-data architecture features compute, storage and cloud services layers that scale independently, enabling any user to work with any data, with no limits on scale, performance or flexibility.

So I love Tableau and I also hold it to a very high standard – static parameters and sets always stick out like a sore thumb, because these objects have so much potential.

Solving business problems likely requires you to combine data from multiple sources. More often than not, those sources are quite different and do not even exist in the same database.

Very often it is needed to visualize data in an historical form. On the other hand most of the time storing data directly in historical form is inefficient and requires duplicating the same data for every historical point.

The problem is to plot two bars side by side, based on two different measures, on a date(/time) axis. For each measure, the ‘date’ axis has the same value, so the out-of-the-box effect in tableau is to have piled up bars.

Tableau interprète les dates différemment entre un fichier en direct et un extrait, qu'il soit créé sous Excel ou en format CSV. Comment l'amener à corriger ceci ?

Python User-Defined-Functions (UDFs) have become available in Public Preview in Snowflake. They allow you to write Python code and call it within the Snowflake UI, just as if you were writing and executing SQL queries.

In the context of the Plegde 1% initiative Argusa supports Globlivres with 1% of its profits.

Artificial Intelligence (AI) projects can be time consuming and complex to build. Einstein is an intuitive tool that aims to facilitate AI-driven decision making. People of all skill levels can build models without having to code.

MakeYourData - MKYD - is a standalone software tool developed at Argusa that allows you to anonymize data and generate synthetic data.

Synthetic data is a new trend emerging in the analytics world. It is artificially created data, often with key properties accurately injected. Several companies have been founded in recent years around the subject of synthetic data and Gartner estimates that it will soon reach the tip of the hype-cycle.