Big Data (BD)

Big Data refers to large-scale data architectures that employ tools which take on the new requirements of data management.

Traditional databases (data storage) assume that data is organized into rows and columns and that data-cleansing methods are in use while volumes of data grow over a period of time, normally, they do not have large-scale data processing. Traditional database/storage systems were designed to take on smaller volumes of data structure, with predictable updating and a coherent data structure. They run primarily on a single server; increases in data volume generate operational costs.

Big Data is coined as such because of the characteristics pertaining to the data that it handles: large volumes, high-velocity generation of data, an increasing format assortment, as well as varying growth patterns and data uncertainty.

The act of extracting value from information is called Data Science, it unites the combined abilities of programming, mathematics and statistics to a specific area of knowledge (medicine, hydrology, finance).  This value is then converted into insights, actions or decisions.

The water sector can benefit from integrating this technology, primarily in gathering data related to water quantity, quality, consumption and the state of infrastructure throughout all of the water cycle. This enables a more efficient analysis of information that allows for a sustainable management of water, improved distribution, and the prioritization of preventative and corrective actions.

For example, a solution has been proposed to predict useful water stress indicators for the agricultural and forestry sectors called FORWARD (Operational Monitoring and Forecasting System for Resilience of Agriculture and Forestry under intensification of the Water cycle) so as to investigate, develop and configure a software tool that is capable of identifying and collecting ecohydrological variables from open data sources.


  • Martinez J. Getting to know the benefits of BigData and Cloud Computing. Free University of Colombia. 2017
  • B. Sarmiento. BigData tools and background. 2014

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