BIG DATA

BIG DATA

1. Characteristics

   • 7 V's
     • Volume
       • Terabytes
       • Petabytes
       • Exabyte
       • Zettabyte
     • Variety
       • Semi-structured data
       • Unstructured data
       • Structured data
     • Veracity
       • Accuracy of calculation
       • Data accuracy
     • Velocity
       • oading speed
       • Processing speed
     • Viability
       • Analyze
       • Select
       • Monitor
     • Visualization
       • Tableau
       • Google Data Studio
       • Power BI
     • Worth
       • Profitable
       • Efficient

2. Definition

   • “Big data is a new generation of technologies and architectures designed to economically extract value from very large volumes of a wide variety of data, enabling its capture, discovery and/or analysis at high velocity”. (Gantz & Reisel,2012 citado por Márquez, 2022,p.245)
   • Big Data typically refers to the application of a practical scientific approach to solving data problems in which one or more of the three main attributes need to be efficiently addressed: volume or quantity of data, variety in origin and speed of generation.(López Murphy & Gonzalo, 2017,p.56)
   • “Doug Laney attempted in 2001 to characterize the fundamental features of big data and, in search of a definition, proposed <<the three Vs>>: volume, variety, velocity.” (Laney,2001 citado por Holmes, 2018,p.25)
   • “Big data is understood as the set of strategies, technologies and systems for the storage, processing, analysis and visualization of complex data sets” ( Casas et all., 2019,p.34).

3. Origin and Background

   • The term data has its origin in the 18th century with the scientific revolution driven by intellectuals:
     • as
       • Priestley
       • Lavoisier
       • Newtom
       • Gauss y Laplace en 1809
         • They established the statistical and mathematical foundations on which studies are currently based.
     • that helped
       • Mapping the spread of Broad Street cholera, a study conducted by physician John Snow who collected a large amount of data.
         • However
           • It was not until the 21st century that the concept of Big Data was introduced, especially in scientific fields.
             • But
               • It was not until the end of the first decade of the 21st century that the Big Data concept was adopted and its use in the business field grew exponentially.
                 • Through
                   • Articles published by tech giants such as.
                     • Yahoo
                     • Google 2003 and 2004
                   • The environment of science
                     • Particularly
                       • Astronomy
                       • Genetics

4. Implications

   • The data will be distributed across different machines, and also stored in different formats from social networks, web pages, government data, etc.
     • Negatives
       • Privacy of personal data at risk
       • Ethical data management at risk
       • National security at risk
       • Identity and Singularity at risk
     • Positives
       • Technological advances
       • Advances in medicine and health
       • Advances in politics
       • Advances in finance
       • Advances in the industry

5. Big data motivation

   • System quality
   • Quality of information
   • Quality of service
   • Benefits perceived
   • Big data
   • Advances in technology
     • Data storage
     • Data processing