Understanding Data-science with Spirituality

in #data8 years ago

Data Science and Spirituality.jpg

Some might find the title a bit weird or even controversial. However, to me there is a solid existence of Datascience in Spirituality and vice versa. The biggest commonality in between these two sciences is the concept of centrality.

It is one of the basic and the most fundamental concepts in statistics that helps statisticians to declare if a particular outcome is significant or not. Similarly, in spirituality the concept of centrality has its own physiological, religious and metaphysical significance. Also, it is worth mentioning that “Center” is referred to as “Balance” in both Data and Spiritual sciences.

In this article I have tried to illustrate some commonalities in between an integral part of spirituality and datascience i.e. “Meditation” (popularly practiced as Kundalini Yog) and CRISPDm methodology aka Cross Industry Standard Process for Data Mining. It is one of the most talked about data mining approaches that data scientists and data mining experts use to tackle data related problems with a common goal as compared to a Kundalini Yoga practitioner i.e. enlightenment, insights and self-awareness in terms of spirituality and business-awareness in terms of data science.

Both of these methodologies focus on cleansing, cleansing or healing of chakras and data cleansing by imputing numbers. Kundalini Yoga is a phased approach which is very similar to CRISPDm method.

I hope the readers will enjoy this interesting comparison.

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This was really informative! I've just started meditating with a group and these terms are all new to me. This explained a lot. Thank you :)

Thanks....I am glad that you liked it and found it informative. Being a data science enthusiast, for me it is a must to meditate to decompress and be ready for the next challenge !!!!

With a high-stress job like that, I can imagine!

It's interesting how the top two levels, which correspond to the levels of consciousness yet to be mastered, also correspond to a more proactive approach to data analytics, related to predicting things and applying foresight, rather than just understanding what's already manifested.

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