- Amazon As college students, we utilize Amazon as our fast shipping shopping spree. From credit card numbers, address and phone numbers, Amazon collects valuable data through every stream of data you use. Amazon based its big data on a four-step process: collect, store, process & analyze, and consume & visualize. Amazon collects raw data from transactions, logs, mobile and more to allow developers to ingest a wide variety of data. After processing the data, it becomes secure and scalable to become a consumable format. The resulting data set is stored for the process for business intelligence consumption and data visualization. All the data assets allow for a fast and easy exploration of options for your soon-to-be empty wallet. The accessibility of big data is used effectively and efficiently.
Big data drives Netflix to BIG SUCCESS. Have you noticed the recommendation hits the spot to your movie addiction? Netflix uses big data for predicting viewing habits, finding the next smash hits, and providing the best experience for the consumers. This is probably why a lot people are in love with Netflix! Data is observed and modeled as soon as you stream, select, and playback stop whatever you are viewing to build a better recommendation list to ensure customer’s satisfaction. Netflix uses tags to suggest other films you may like and “suggest” it to you. The more people gossip about a show, Netflix will definitely have it on its platform for you to stream.
Don’t you love the refreshing drinks Starbucks provides? Starbucks probably knows how you like your coffee. Starbucks uses data analytics to not only determine optimal store location, but to customize its menu offerings by location and therefore capture your preferences. Starbucks leverages data from Atlas, an in-house data mapping software to carve data on consumer demographics, population density, income levels, auto traffic patterns, public transport stops, and the types of stores / businesses in the location. Through the analysis of the data, Starbucks is able to predict foot traffic and average customer spend of a given location, therefore helping Starbucks to determine the economic viability of opening a store in that spot. This also creates value for customers by providing convenient locations to grab that much-needed cup of java. Also, it helps Starbucks determine tailored menu offerings. These data-driven menu offerings offer additional ways to capture value beyond just charging a premium on coffee.
Remember those times, when we distract ourselves with some fun games on Miniclip? Man, those were the days. Miniclip centralized their data to get a better understanding of their gamers. Miniclip uses a cloud analytics platform to monitor and improve user experience. Customer satisfaction is a priority for Miniclip. Big data reporting, analysis, experimentation and machine learning allow the company to measure the successful elements of their products and implement better strategies for future ventures while eliminating or improving the problematic components. By using big data, it makes games more profitable, fun, and supports business growth.
T-Mobile is the third-largest phone carrier in the United States. T-Mobile succeed through the help of big data, more specifically -social media. It used big data to analyse and predict consumer fluctuations. By analyzing past transactions and managing customer relations, the company uses sophisticated predictive models in place of traditional business intelligence-based hindsight customer’s behaviors.