{"id":36,"date":"2020-04-29T13:45:43","date_gmt":"2020-04-29T13:45:43","guid":{"rendered":"http:\/\/likeshares.in\/blog\/?p=36"},"modified":"2020-04-29T13:45:43","modified_gmt":"2020-04-29T13:45:43","slug":"the-scope-of-data-science-big-data","status":"publish","type":"post","link":"https:\/\/imageconindia.com\/blog\/2020\/04\/29\/the-scope-of-data-science-big-data\/","title":{"rendered":"The scope of Data Science\/ Big Data"},"content":{"rendered":"\n

Data Science\/ Big Data is the new concept revolving around. There are various importance of data science in the technological world. To grasp about what data science is and about its scope, continue reading <\/p>\n\n\n\n

What is Data Science?<\/strong><\/p>\n\n\n\n

Data science keeps on advancing as one of the most encouraging and sought after vocation ways for gifted experts. <\/p>\n\n\n\n

Data science<\/em><\/strong> is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information. The goal of datascience is to gain insights and knowledge from any type of data \u2014 both structured and unstructured.<\/em><\/p>\n\n\n\n

Who\u2019s the father of Data Science?<\/strong><\/p>\n\n\n\n

The term “Data Science” was coined at the beginning of the 21st Century. It is attributed to William S. Cleveland who, in 2001<\/p>\n\n\n\n

Where Data Science is implemented \u2013 Applications? <\/strong><\/p>\n\n\n\n

There are various budding trends in Data Science which has got its own reach, few of them are<\/p>\n\n\n\n

  1. Image Recognition<\/strong><\/em><\/strong><\/li><\/ol>\n\n\n\n

    You upload your image with your friends on Facebook and you start getting suggestions to tag your friends, this automatic tag suggestion feature uses face recognition algorithm. Similarly, while using WhatsApp web, you can scan a barcode using your phone. All these comes under image recognition and Google provides you the option to search for images by uploading them. The image recognition technique is implemented in this case.   <\/strong><\/p>\n\n\n\n

    • Fraud and Risk Detection <\/strong><\/em><\/strong><\/li><\/ul>\n\n\n\n

      This application was come up by the finance department.\nThe companies faced debts and losses every year. But they had lot of data of\nthe individual using the initial paper work. There Data Science came in role to\ncome up from the losses. Over the years. The banking sector dealt with all the losses they faced via customer profiling, past expenditure and\nother essential variables to analyse the probabilities of risk and default. <\/p>\n\n\n\n

      • Gaming <\/strong><\/em><\/strong><\/li><\/ul>\n\n\n\n

        Games nowadays are designed using machine learning algorithms which improve as well as upgrade themselves as the player moves up to a higher level. In motion gaming also, your opponent which is the computer analyzes your previous moves and accordingly and then shapes up the game.<\/p>\n\n\n\n

        There are various applications of Data Science in this technological world, which has got its own importance to be dealt with. <\/p>\n\n\n\n

        Why Data Science is needed?<\/strong><\/p>\n\n\n\n

        Data Science is needed for various platforms for different functions. It is fairly common for the Data Scientist to have previous experience in infrastructure design, cloud computing, and data warehousing. <\/p>\n\n\n\n

        1. Data Science enhances management and officers to make better decisions.            <\/li>
        2. It is used for better marketing purpose. <\/li>
        3. For enriching peoples life and giving way for new innovations<\/li><\/ol>\n\n\n\n

          Popular Data Science Jobs<\/strong><\/p>\n\n\n\n

          There\nis a huge vacancy out there in the industry for the ones who holds knowledge on\nData Science. The corporate world is ready to hire predominantly talented\npeople with keen knowledge about IoT. Few of them are <\/p>\n\n\n\n

          1. Data\nand Analytics Manager<\/li>
          2. Data\nArchitect <\/li>
          3. Principal\nScientist <\/li>
          4. Data\nEngineer<\/li>
          5. NLP\nEngineer<\/li>
          6. Data\nEngineer Designer<\/li><\/ol>\n\n\n\n

            Grab hand full of opportunities once you gain knowledge about Data Science. <\/p>\n\n\n\n

            <\/p>\n","protected":false},"excerpt":{"rendered":"

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