Data Science.

Data Science.

1. A field of study where scientific and analytical principles are applied to extract valuable information from massive data banks in order to make better decisions.

   • Data science seeks new questions and new models for approaching information.
   • Skills: math, advanced statistics, predictive modelling, machine Learning, programing, expertise on data bases, etc.
   • Application: Processing and verifying data, machine learning, algorithms, predictive models.
   • Big data: By not limiting itself to a single field, it has a multidisciplinary approach, where scientific and statistical principles are applied to treat and process data, determine new models and develop advanced algorithms.

2. Data Analytics.

   • It uses existing information to answer and solve today's problems, a much more specific approach to a goal to be achieved under a certain model for problem solving.
     • Responsible for solving difficult problems under proven models and methods.
     • Skills: Problem solving, excel, statistics, python.
     • Application: Data cleansing, pattern identification, data analysis, visualizations, KPIs.
       • Big data: Big data: It has a specific objective and a framework already validated to be applied to any data set, its main objective being to maintain data-driven decision making, based on patterns, trends or any uniqueness identified in the information.

3. Big data: Extremely large data set.

   • Basic characteristics: volume, variety, velocity, veracity.