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Big Data

Hey! What is tonight's menu? How about some Peanut Broccoli Noodles or Pizza cupcakes? Or maybe something lighter with onions, apricots, or maybe some avocado? Food choices can be so varied depending on the personal preferences of different individuals. The flavor and richness of food recipes are believed to have long been based primarily on the human experience. Making a recipe that will please one's palate takes years of experience. But hold on to that thinking, it may be a tad hard to digest, but indeed, Big Data is becoming revolutionary in the development of human food recipes. With the power of analytics, many combinations can be tried and new customized recipes can be created.


Let's see the aspects involved when creating variants of Chocolate Chip cookies using BigData. Below is the traditional chocolate chip cookies recipe which is passed on from generation to generation without any major modification.


This recipe won't be useful for individuals having nut allergies,  vegetarian food ingredients preference, or gluten-intolerance. Also, some individuals would want to add some more variations like berries or hazelnut to the cookies. But how do we customize the recipe based on individual preferences? This is where Big Data Analytics comes into play due to the below features-

A] Data-based decisions: 

Based on the data points gathered from various google searches, regional demographics, and other related information, big data analytics can help in suggesting recipes or modifying the traditional recipe with alternatives more suitable to the preferences. An additional feature could be recipes with the ingredients present in a particular region. So if any individual has vegan food preference, the above cookie recipe would come in with an alternative to use almond milk or soya milk along with skipping eggs and adding a banana or any other vegan alternative available locally.

 

B.] Quick turnaround with all possibilities

Using AI(Artificial Intelligence) it is possible to produce all possible combinations of a recipe with a quicker turnaround as compared to manual turnaround time. In the above cookie example, an AI-enabled platform will help bakers discover new flavors faster by predicting new flavor combinations through data about sensory research, customer preference, and flavor palettes from millions of data points. This would lead to faster discovery of new flavors and help us enjoy more variety of food in this lifetime.


This was just a small example explaining the use cases of using BigData in the food industry. However, we should not forget that BigData highly depends on the information collected from processed data. Hence, unless the information is shared and analyzed across the media chain, from the manufacturer to the customer, the full power of big data will not be realized. However, considering the rate at which the Technology industry is disrupted, I am confident that BigData Analytics will soon be an integral part of this industry. The right balance of BigData Analytics and human experience can revolutionize many facets of the industry in no time. While this is revolutionizing, let me manually try out combinations and modify the traditional recipe and bake a batch of 'BlueBerry Chocolate Chip' cookies.

 





References:

https://www.bigdataframework.org/data-types-structured-vs-unstructured-data/

https://blog.cdw.com/software/a-recipe-for-successful-data-analytics

https://blog.cdw.com/software/a-recipe-for-successful-data-analytics

https://www.foodbusinessnews.net/articles/14045-big-data-offers-big-opportunities-for-food-and-beverage

https://in.pinterest.com/search/pins/?q=cookies&rs=typed&term_meta[]=cookies%7Ctyped



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