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Lecture 2 (Characteristics of big data (Veracity (high quality data needed…

- - - - can be partially understood by computers and humans
      - eg. HTML (hyper text markup language)
      - textual data with a discernible format for automatic processing
    - - Data not easily understood by computers but humans can understand easily
      - Multimedia content eg. images, video, pdf
      - No inherent pattern
    - - data needs to conform (computer will check if data conforms to the formats like in Excel 12/05/97 means date)
      - Data can be processed automatically by computers eg. student records name matric number grades or company's inventory
      - predefined data types (eg. whether data is whole number/got decimal points/texts/email/dates) and formats (eg. dates-->write 12.05.97 or 12/05/1997 or 12 may 1997
  - - - Traditional/non-traditional
        
        traditional-->data stored using existing technology
        
        non-traditional-->data using technologies that have been created especially to cater to big data
      - Within/outside organisation
        
        within-->data generated by the org itself eg. org that keeps track of all the online transactions that have been made by people/ org generates database of employee records
        
        outside-->data generated by other ppl eg. customer feedback on product, social media postings by other ppl about the company
- - - - determine what will likely happen in the future
      - based on past data
    - - use both descriptive & predictive analytics to create alternatives & determine the best
      - determine best possible decision
      - eg. retail industry
    - - understand underlying trends & causes
      - generate queries, reports, alerts (eg. SMS notification can be sent to u if stocks go down or smth)
      - what is happening
  - - - need to be able to capture store and retrive data effectively and efficiently
      - Hence new technologies & skills needed
- - - - strong competition among orgs
      - use analytics to make good data-driven decisions
    - - everyone is using analytics so we better use it
- - - - Data scientists
        
        ppl with strong analytical skills
        
        handle big data and apply analytical techniques
      - Technology professionals
        
        plan,design, implement & support analytics software