Data clustering is the classification of data objects into different groups (clusters) such that data objects in one group are similar together and dissimilar from another group. Many of the real world data clustering problems arising in data mining applications are pair-wise heterogeneous in nature. Clustering problems of these kinds have two data types that need to be clustered together. In an industrial setting, despite collecting data from tens of thousands of sensors, less than 1% is actually utilized. We can move rapidly into Industry 4.0 by combining subject matter expertise, data collection methods and next-generation data science tools, beyond many of the “me too” products.