Big Data, Data Analytics, Data Science - all these terms make a noise in the world! Here are a few examples to clarify the difference and avoid messing them up:
- Google has a number of successful products, Data Science Algorithms embedded within. For instance, all the digital marketing tools, like AdWords, AdSense, DoubleClick and Google Analytics, - use data science algorithms analyzing Internet searches to assist its users with their advertising activities, SEO strategies, analytical researches and understanding their visitors behavior patterns.
- LinkedIn is the professional network injecting Big Data Analytics into various features to deliver their users really smooth experience. For example, such features as 'People You May Know', 'Skills Endorsement' and 'Jobs You May Be Interested In' are based on analyzing a huge amount of initial user data both structured and unstructured: skills, previous jobs, In-Mails, groups etc.
- And about Big Data itself: literally this buzzword means huge volumes of information (structured and unstructured) demanding cost-effective and innovative processing in order to drive insights and improve decisions making.