Standardizing the Data Science Process for Better Results-IABAC Imagine a team excited by new data. They start working, but months later have nothing useful to show. This is common. In fact, one analyst from Gartner reported that around 85% of big data and AI projects end in failure. If airlines only landed 15 out of 100 planes, no one would fly. The same logic applies here: without a clear process, data science efforts often miss the mark. The...
0 Acciones
835 Views
0 Vista previa