The Risks of Data Intelligence for Digital Transformation

The manner in which you train your data science systems to perform whatever analysis they're performing, or perhaps even to perform whatever autonomous decision making responsibilities. That needs the greatest amount of attention to make sure that it's as pure and relevant and appropriate for whatever the data intelligence is intended for. Bad data, data bias, flawed data, inaccurate data, all of those factors can influence the quality of data intelligence. If it's low-quality data intelligence, we can't expect high-quality results. So the more data intelligence we have going on, and the more we understand what the information means, the lower the risk is going to be for digital transformation.