Do you believe you are knowledgeable about data science? See how Amazon has built an entire business model around it! It has been four months since you purchased that top. 

According to sources, more than half of all new businesses fail within the first year. 50% of startups fail within the first five years, and 66% fail within the first ten. The main reason for this failure is that startups are extremely risky, and there is a lack of innovation on the part of both employees and employers (sometimes)

Amazon, headquartered in Seattle, Washington, is a multinational technology company. E-commerce, cloud computing, digital streaming, and artificial intelligence are its primary focus areas. It is one of the Big Four Technology Companies, along with Google, Apple, and Facebook, and the driving force behind all of these companies' global dominance is INNOVATION. It is always two steps ahead of the competition and understands its customers better than any other company.


How Amazon makes use of data science:

  1. Employs a recommendation-based system (RBS) -

It collects data from its customers using this technology (Which can also be called Big Data). The more data they have, the better because once they understand what the user wants, they can streamline the process and encourage customers to buy the products. RBS seeks and predicts a user's "rating" or "preference" for an item.


Data science assists Amazon in understanding customer needs, and instead of customers searching for similar products, the products are provided in the recommendation. This is accomplished through the use of collaborative filtering. While you search for products, it attempts to build a profile of you. It has many such profiles and serves you the product that people with similar profiles have purchased using collaborative filtering. To learn more about the recommendation system, doc checks out the machine learning course in Mumbai.

  1. Tracking the user to understand their mindset-

It keeps track of almost everything, starting with your needs, what you've searched for, what you'll need in the future, and your personal details (like contact number and address), and through the address, it tries to understand the user's income level, so it knows what products to offer and what not. It also monitors and studies the feedback habits of its users.

  1. Comprehensive understanding of technicalities (habits)-

Amazon attempts to understand browsing habits and the amount of time spent on each platform. An external database is also used. All of this is handled by Amazon's central data warehouse.

  1. Faster shipping process-

Amazon has dramatically simplified the shipping process. It has progressed to the point where it can predict who will order what and when using big data analytics insights. This has improved the online shopping experience. This is because Amazon wants to be able to deliver products more quickly. This is accomplished by:


(I)Prognostic analytics:

Based on past purchasing patterns, social media analytics, and weather forecasts, this helps to ensure that the right items are in stock. This has definitely resulted in products being delivered quickly.



This "air mail" has yet to enter the mainstream, but it, like everything else, faces challenges. The cost is prohibitively high; all we can do is wait for new technology and keep looking up in the sky.

This demonstrates how Data Science technology is taking over and how commercial companies can make accurate predictions. The products that are ordered will be delivered to the customer quickly.


Are you a data science aspirant, looking for resources to learn? Learnbay has a domain-specific data science course in Mumbai, designed to meet industry demands. 

Visit the site for more information.