miércoles, 4 de enero de 2017

Data Science Unleashed

In today’s world, data science has immensely grown across a multitude of industries including finance, energy, travel, and government, but even more importantly, universities have begun to recognize the importance of offering courses and programs in this field.
Data Science and Analytics will continue to be one of the cornerstones for innovation as the businesses explore its revolutionary potential to transform business processes, generate new business models, boost operations’ efficiency and catalyze innovation.

Data Science is a multidisciplinary field that involves processes and systems to extract knowledge, focused on the future by performing exploratory analysis to provide recommendations based on models identified by past and present data, representing high value for the business.

While data science asks:
What will happen next? And What should be done to prevent...?

The data analysis asks: what happened? And Why did it happen?

The following table explains the differences with respect to processes, tools, techniques, skills and outputs:

Analisis de Datos
Ciencia de Datos
Looking backward.
Looking forward.

Naturaleza del Trabajo
Report and optimize.
Explore, discover, investigate and visualize.

Reports and Dashboards.
Data Product.

Herramientas usadas
Hive, Impala, Spark SQl and HBase.

MLib and Mahout.
Técnicas usadas
ETL and exploratory analytics.

Predictive analytics and sentiment analytics.
Habilidades Necesarias
Data engineering, SQL and programming.

Statistics, Machine Learning and programming.

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