The main goal of my team is to make sure that our customers achieve their full potential through data, analytics, and technology. To help them realize that full potential, we help them design solutions that remove silos between people - the primary assets of an organization - all the data they have carefully collected throughout those years and technology while respecting the governance frameworks in place internally. Removing those silos help our customer build more analytics projects in a year than their traditional analytics stack would allow them to do.

It is an excellent question that falls right under the explainable AI topic. For some use cases, the answer might not be easy to interpret or may cause some ethical challenges. At Dataiku, we believe that building a predictive model should be done in a human-centric way. This way it ensures that the full context has been taken into consideration and validate by different individuals, intellectually or ethically equipped to interpret the result of the machine. The machine can speed up the analytics process and make us humans more productive. But ultimately, we build AI models to support our decision process in front of the most difficult task.5. 

The pandemic has accelerated the transition from the physical to the digital world. With everyone spending more time at home, a lot more data are collected through IoT devices, mobiles, tablets, and most of the business is done online. E-commerce, banks have greatly benefited from it and a lot of organizations have greatly improved their infrastructure to better serve their customer that way. They capture data better, more quickly and they can make better decisions thanks to the right analytical stack to create a virtuous circle based on analytics

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