We enable organizations to deal with the plethora of challenges, some of which are a function of the characteristics of big data, some, due to the existing analysis methods and models, and some, by the limitations of current tools. To facilitate data-driven decision making, organizations need efficient methods to process large volumes of asserted data into meaningful comprehensions. We help organizations in facilitating exact such decisions with the help of descriptive, inquisitive predictive, prescriptive and pre-emptive types of data analytics support. As more and more organizations are practicing data-driven culture, the wheel of data science processes is getting more elaborative. In addition to the classical components of the data science execution model, the need for bias detection, correction, and explainable AI has become evident. Just like bias in the models can lead to lethal consequences, providing just the probabilities of a phenomenon is no longer sufficient as it have become equally important to understand the rationale behind every recommendation. At Empirisch Tech, we develop bias aware explainable machine learning models to help facilitate not only the predictive form of data analytics but the prescriptive and pre-emptive analytics as well.