Big data

Big data

1. Origin

   • The origin of big data is related to several events over time, mainly, with the increase in the magnitude of data where the need for new tools to store and process these large amounts of data efficiently started to become evident. The events that mark the beginning of big data in a more formal way, taking into account that there are other past events that established the foundations, was the beginning of the collection of demographic data and then the use of the first tabulating machine for its processing in the nineteenth century.

2. Implications

3. Main Definitions

   • There are different definitions of big data, however, these always revolve around the characteristics of the data that are the object of study, which are encompassed in what is known as the Vs; and the methodologies and technologies used to manipulate them.
     • “An information asset whose volume is large, velocity is high, and formats are various”. Gartner (Sedkaoui, S., 2018)
     • "Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight decision-making and process automation"
     • “Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data" Research firm McKeinsey (Sedkaoui, S., 2018).
   • The Vs used to define big data are the following: (Sedkaoui, S., 2018)
     • Variability
     • veracity
     • Validity
     • Vulnerability
     • Volatility
     • Visualization
     • Value
     • Volume
     • Velocity
     • Variety

4. Motivations

   • Initially causality was the motivation: the cost in time and money for processing data to establish the cause and effect relationship
     • Motivation then changed to establish correlation between variales of the sample (Casas Roma, Nin Guerrero, 2019)

5. Bibliografía

   • Casas Roma, J. Nin Guerrero, J. & Julbe López, F. (2019). Big data: análisis de datos en entornos masivos: ( ed.). Editorial UOC. https://elibro-net.bibliotecavirtual.unad.edu.co/es/ereader/unad/117744?page=26
   • Sedkaoui, S. (2018). Data Analytics and Big Data: ( ed.). Wiley. Recuperado de https://elibro-net.bibliotecavirtual.unad.edu.co/es/ereader/unadenglish/186085?page=40.