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The old saying, GIGO-garbage in, garbage out, stays relevant even today with the world of fast evolving technologies. In particular, the world of data-AI is no different. Your AI projects are majorly impacted by the quality of data and therefore data has to be "ready" for AI. What might be relevant for one particular AI project might not be relevant to another. Getting your AI project to deliver the right outcomes is  dependent on the processes brought to the table with the data in question. 

The old saying, GIGO-garbage in, garbage out, stays relevant even today with the world of fast evolving technologies. In particular, the world of data-AI is no different. Your AI projects are majorly impacted by the quality of data and therefore data has to be "ready" for AI. What might be relevant for one particular AI project might not be relevant to another. Getting your AI project to deliver the right outcomes is  dependent on the processes brought to the table with the data in question. 

To learn more about how data can be ready for an AI project and what are the steps involved, read this article by Gartner: https://www.gartner.com/en/articles/ai-ready-data 

To learn data analytics including free training and certifications, visit qlik.com/academicprogram 

The Qlik Academic Program is being leveraged for getting trained in cutting edge data analytics technologies by more than 3300 universities and educational institutions worldwide.