Apple, LinkedIn, Netflix’s Big Data Statement
Big Data Proving its Worth
INTRODUCTION
We live in a digital world where a large amount of data that goes beyond the size of Petabytes and Exabytes is gathered by companies that come through multiple sources like social media, trading, customer feedback, healthcare, education institutes in the form of comments, likes, videos, audios, files, XML, binary, etc.
These figures about Big Data will give you a deep insight into the amount of data that we are surrounded by today.
- 63,000 web searches are made on Google per second.
- 500 Terabytes of data is generated on Facebook per day through its 2 billion active users.
- 12 Terabytes of data is generated on Twitter per day.
- Snapchat users share 527,760 photos/minute.
- More than 120 professionals join LinkedIn per minute.
- Users watch 4,146,600 YouTube videos per minute.
- Instagram users post 46,740 photos/min.
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TOP COMPANIES BIG DATA ENDEAVOURS
Apple
Apple was a late entrant in the world of Big data, but the entrance of Apple with its iWatch has brought the wearables into the mainstream. With iWatch, Apple collects all the data about the user through its sensational sensors.
Data is collected about how, when and where its products — iPhones, Macbooks, iPads, and iWatches are being used. Based on this information they decide which new features should be added and how the way they are operated can be tweaked to provide the most comfortable and logical user experience.
Apple’s Siri collects the voice data from all its users and tries to analyze them to map the users to the information they are seeking for. This data is being used to provide the user with the information by improving their speech recognition patterns.
With its iWatch, Apple has tied up with IBM to facilitate the development of health-related mobile apps. With this Apple wants to monitor the health of all customers and to improve the lifestyles and has saved many lives till now.
iTunes is yet another example where Apple is using the Big data analytics to analyze the music taste of customers and to provide them the suggestions as per that.
It’s high time to choose Big Data
LinkedIn has a user base of more than 575 million and by this, you can imagine the amount of data it handles regularly.
With Big Data, LinkedIn has developed many products or services that help users to connect and find more useful people and jobs at the times they need it.
Some of the services that LinkedIn uses are:
- People You May Know
LinkedIn collects user data like login details, in-mails, applied for jobs, profiles viewed, browser settings, etc. to run the jobs that analyze the data and provides the user with suggestions about the people they may want to connect with. LinkedIn has 5 test algorithms continuously running that generates 700 GB of output data for the “People You May Know” feature. - Skill Endorsements
This is the most helpful feature of LinkedIn that is vital for many recruiters to extract the best suitable resource they can hire. A user can endorse another user in their network for a skill that is displayed as “Skill & Endorsement”, on the user’s profile. - Jobs You May Be Interested In
90% of Fortune 100 Companies use LinkedIn to hire top talent and 89% of the professionals use LinkedIn for job search. Around 50% of the website’s engagement comes from this feature and Big Data has been the backbone of it.
Using Big Data and machine learning, LinkedIn displays Job suggestions to the users as per the user’s profile settings and their search history.
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Netflix
Netflix has become the king of online streaming with the help of Big Data and analytics. Netflix has more than 100 million subscribers and they use the data from these many users to provide their users with the recommendations that have influenced 80% of the content watched on Netflix. Netflix member loses interest after 60 to 90 seconds of choosing something to watch, having reviewed 10 to 20 titles and this is the amount of time that Big Data analytics utilizes to its best. There are typically about 40 rows on each homepage and up to 75 videos per row.
Netflix gathers all the data from ratings, searches, date on which movie/show was watched, on which device it was watched, when a program is paused, do the credits get skipped, etc.
Netflix spent 100 million dollars on House of Cards which has been boon to it as they were able to attract many subscribers by using Big Data analysis.
Netflix tries to find the next smash-hit series for its viewers. Orders the entire Netflix collection for each member profile in a personalized way. The same genre row of each member has an entirely different selection of videos.
Netflix then picks out the top personalized recommendations from the entire catalog, focusing only on the titles that are top of the ranking.
Sort’s customers recently viewed titles and estimate whether the customer will continue watching or re-watch, or whether perhaps they stopped watching something because it was less interesting than they envisaged.
Netflix recommends similar videos just because you watched one video you may also like similar videos. Even though the similarity ranking is not personalized, it provides a good estimate of what a member might like based on what they previously watched.
EndNote
With giant companies like Apple, LinkedIn, and Netflix which are the undisputed kings of their respective domains are now bound to introduce Big Data analytics into their organizations itself speaks volumes about the stature that Big Data has gained globally.
I don’t there’s anything that can define the importance of Big Data better than this.
So, what are you waiting for then?
