Big Data Companies To Start your Bright Future
Explore different domains and companies using Big Data for gaining insights.
Big Data refers to the vast volume of data which is difficult to manage using traditional database techniques. This data can be either structured, semi-structured, or unstructured. Big Data has innumerable benefits. It has tremendous potential for improving human lives. Big data can create connections, identify hidden patterns, and finds use in innovations like improving medical treatments, developing self-drive cars, accurate weather predictions, and many more.
The article provides you the complete guide about the different Big data companies. The article enlisted the number of companies using Big Data. It first gives you a short introduction about rise in Big Data. The article then explains how different companies are using Big Data to gain insights.
Big Data Rise
People are becoming more digitized. Earlier a person goes only for swimming but as of now he knows about calories he would be burning, pulse rate, heart rate, time, distance, etc. Using these readings, he can compare this to his previous performance as well. All these are because of advancements in technologies. Big data seems to be growing exponentially and penetrating wide sectors and industries with every passing day. Thus, Big data keeps getting bigger.
Every day, 2.5 quintillion bytes of data are produced. It has been said that for downloading the total data available online, we will require around 181 million years.
Social media, e-commerce, and search engines are significantly contributing to this high volume of data.
Approx, 33% of the time that users spent online are on social platforms.
Twitter users every minute sends half-million tweets.
Google records a search volume of 1.2 trillion yearly, with 40,000 search queries being submitted every second.
The data on YouTube servers has exceeded 1 billion gigabytes.
Smart devices such as sensors, fitness trackers generate 5 quintillion bytes of data daily.
These rising Big Data provides tremendous opportunities for companies to become successful and gain profits.
Let us explore different domains where Big Data is used by companies.
Big Data Companies – Top Companies using Big data
There are vast amounts of companies using Big Data. Here I am listing some top companies that use Big Data to gain profits and improve customer experiences.
1. Amazon (“Everything under one roof”):
In today’s consumer landscape, Amazon is an e-commerce giant. Amazon’s success does not come by an accident. Amazon becomes successful because it utilizes the advantage of big data to make decisions, please customers, and stimulate purchase.
Amazon has access to the vast amount of data of its customers like customers’ names, addresses, payments made by customers and search histories. All this information is filed away in its data bank. Amazon uses this information to improve customer relations which are overlooked by many big data users. It uses Big Data gathered from customers to fine-tune its recommendation engine. The more it knows about you, the better it can predict what you want to buy. And, once any retailer comes to know what you might want, they can streamline the process of impressing you to buy it.
Amazon is a leader in using CFE a comprehensive, collaborative filtering engine. It analyses what items you purchased earlier, what is in your wish list and online shopping cart, products which you reviewed and rated, and different items you search for most. It uses this information to recommend additional products purchased by other customers while buying those same items.
For example, when we add a DVD to our online shopping cart, then similar movies that other customers purchased are also recommended to us for purchase.
Thus, in this way, Amazon uses suggestion power to attract you to buy to a large extent as a means of satisfying your shopping experience and spending more money. Due to these Amazon generates 35% of the company’s sales annually.
Netflix has surpassed Disney with a company valuation of over $164 billion. Netflix’s success is attributable more to user experience and content rather than marketing. Netflix content is influenced by big data. It uses Big Data to find out what users want to see and give it to them. Netflix gathers user data about:
- The date at which the user watched the content
- The device on which the user watched the content
- Searches on its platform.
- The content portion that got re-watched
- Whether content was paused
- User location data
- Time of the day and week in which content was watched
- Metadata from third parties like Nielsen
- Social media data from Facebook and Twitter
Once the data gets collected, Netflix focuses on giving the user what the user wants. Netflix does so through a personalized content ranker which organizes Netflix user’s collection on the basis of the user personal information collected. Netflix prompts the content based on content popularity as well as the user’s Netflix activity. While promoting “top content” to users Netflix makes sure that it is relevant to the user’s personal interest.
3. American Express
American Express handles about more than 25% of the U.S. credit card activity. Big Data is the heart of decision-making at American Express. American Express interacts with people on both sides that are millions of buyers and millions of businesses. The Company uses big data for fraud detection and bringing customers and merchants closer.
The primary aim of American Express is to detect fraudulent transactions. The company detects fraudulent activities by using a Machine learning model that takes data about card membership information, merchant information, spending details and makes a decision in milliseconds. Also, it uses its vast data flows to build apps for customers which connects cardholders to products or services. One such application called Amex Offers shows the real-time coupons which are relevant to the individual’s buying habits and lifestyle based upon the individual’s physical location and nearby businesses. For merchants, Company offers new online business trend analysis and industry peer benchmarking that helps companies to compare there doing with their competitors.
Check various applications of Big data in different domains.
Starbucks is one of the best-known companies in the world. It has over 27,000+ stores. The secret ingredient for Starbucks’ success is its use of data analytics. Data is key to Starbuck’s success, which includes the head of Global Strategy and Analytics as part of its leadership team. Starbucks says that this function uses “methodologies ranging from ethnography to big data analytics… that helps support Starbuck’s pricing strategy, real estate development planning, product development, trade promotion optimization, and marketing strategy.”
Have you ever wondered how Starbucks opens its three branches on the same street without any business suffering?
Starbucks uses big data to determine potential success in each new location. It collects the location information like traffic in the area, area demographic and customer behavior.
Making such an assessment before store opening enables Starbucks to fairly estimate the success rate. Starbucks chooses locations based upon the tendency towards revenue growth.
LinkedIn is the first largest network that connects professionals and employers all over the world. It is the biggest social network platform for professionals, with 660 million users spread over 200+ countries. As per the November 2019 report, over 30 million companies have profiles on LinkedIn. Every second, more than two new members join LinkedIn.
LinkedIn tracks every movement of the user on the site and analyzes this data to make better decisions and design data-powered features.
It uses big data for its recommendation engine to develop product offerings such as people you may know, who have viewed my profile, jobs you may be interested in, and more. Hadoop is the core component of the LinkedIn big data infrastructure that powers some of the popularly used features on mobile apps and desktop site.
Big Data and machine learning is a backbone for everything on LinkedIn, whether it is Job Recommendations, News Story Recommendations, Group Recommendations, or Personalization of the Social Feed. Some of the services offered by LinkedIn are:
1. People you may know:
LinkedIn collects user data such as contact information, companies users previously worked with, user accomplishments, user interests, user experiences. It stores these data into their warehouse database, and by using its machine learning algorithms, it helps the user to connect to people of its industry, friends and to present him to all people that he could be interested in.
2. Skill Endorsements:
Skill Endorsements in another exciting feature in LinkedIn that recruiters use to hire the best employers. A user can endorse another member in their network, which is then shown on the endorsed person’s profile.
3. Jobs you may be interested in:
Based on users’ search history, skills, and previous experiences, LinkedIn displays the jobs to the user they are interested in.
4. News Feed Updates:
LinkedIn uses data analytics to understand what kind of information users like the most, subjects in which the user is interested, what sort of updates users may like, and aggregate these to put the real-time news feed for the user.
McDonald’s which is the world-famous fast-food joint is also embracing Big Data and Artificial Intelligence. Its updated mobile application allows customers to order and pay via phones. In order to make customers’ experience more enjoyable, they provide exclusive deals to the customers. McDonald’s to gain profits collects essential information about its customers. It collects data about what foods and services customers order, and how often customers visit, or whether they visit drive-thru or go inside. This big data enables McDonald’s to more targeted promotions and offers. It has been found that the Japanese customers who are using McDonald’s mobile application spend 35 percent more because of its spot-on recommendations feature just before they are ready to order food.
7. General Electric (GE)
General Electric is the company that has brought electric lighting and types of machinery to homes and businesses. GE has embarked on its ambitious plan “Industrial Internet” just because of Big Data. GE has installed sensors in machinery like gas turbines, jet engines, etc. General Electric’s power turbines, hospital scanners, and aircraft engines are constantly monitoring the conditions they are operating in. GE uses the data from these sensors to identify the ways for improving working processes and reliability. The reports are passed to the analytics team for developing tools and improvements for improving efficiency.
Swiggy is the best choice for foodies. It is India’s leading online food ordering and delivery platform. At present, Swiggy serves 20+ million users and is present across 140+ cities and still expanding.
Every week Swiggy generates terabytes of data and uses this big data for increasing delivery efficiency and connecting customers to the right restaurant by using rising technologies such as ML and Artificial Intelligence (AI).
Swiggy offers its users a variety of restaurant options and provides fast order delivery right to their doorstep.
It uses data analytics to personalize the list of restaurants at the app homepage based on the user’s tastes rather than just based on the customer’s location. Based on user past orders and searches, it provides the user with the food options of their choice that helps the user to choose their favorite food within minutes.
Miniclip is a company that develops, publishes and distributes digital games globally. It uses big data for monitoring and improving user experience.
Customer retention is the company’s priority for making games more profitable and enhancing business growth. Big Data analysis, experimentation, reporting, and ML data products enable Miniclip to measure the successful elements of their product. It then implements them in future ventures.
Spotify which is the topmost on-demand music service also uses Big Data, AI, and ML for delivering unique and personalized music listening experience. It is definitely a data-driven company. Spotify users daily create 600 gigabytes of data. Spotify uses this data to make its machines and algorithms perfect to improve customer experiences. This helps the Company to extrapolate insights. Also, the company crawls the webs frequently to look for music blogs, posts to understand people’s opinions about specific artists and songs. Some of the ways in which Spotify uses Big Data to create value are:
1. Recommended playlists:
Spotify offers playlists curated algorithmically to its user. It includes music already known by the user as well as music the user is unaware of. Spotify can also curate playlists depending on weather conditions.
2. Discover tab:
Spotify users every week get a fresh new playlist called Discover Weekly. It is a custom playlist that includes new music from the favorite artists of the user. It also recommends artists based on user listening history.
After reading this article, I hope you are now able to understand how Big Data plays a vital role in shaping the company’s market. We have just enlisted only ten companies but almost 80% of the world’s companies use Big Data analytics. No sector, no industry is left behind the use of Big Data. All are deploying Big Data technologies in their organizations to gain insights. This leads to growing demands for professionals having Big Data Skills.
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