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Data Science

  1. Data Science emerged of the prevalence of Big Data
  2. The huge structured, semistructured,unstructured data generated by the emails, social media, online/offline shopping transactions, data generated out of different kinds of online/ofline services, photos, video etc. needs to be analysed for the benifit of the organization/business
  3. Data Science is the continuation of the field data mining and predictive analytics, also known as knowledge discovery and data mining (KDD)
  4. The three components involved in data science are organising, packaging and delivering data. Organising is where the physical location and structure of the data is planned and executed. Packaging is where the algorithms are built, the advance mathematics and statistics are applied and the graphical visualisation is created. Delivering is where all these analyis with simple temrs gets told and the value is obtained.
  5. Advanced mathematics, statistics, business analytics, business intelligence tools are needed to be used
  6. The result of the analysis must reach the non technical audiences
  7. Analytics plays an integral role in the facilitation of Data Science, both during the initial phase of testing unstructured data and while actually building applications to profit from the knowledge such data yields
  8. Data Scientists are qualified people with strength and patience to drill through huge repository of data and the technical skills in writing algorithms to extract insights from these mountain of data

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