BigData

BigData

1. Origin

   • The concept of Big Data Emerges at the beginning of the 21st century in the environment of science, particularly, astronomy and genetics.
   • The Sloan Digital Sky Survey project generated the largest volume of data in the history of astronomy.
   • Need for a new approach to manage and analyze these large volumes of data.
   • Exponential increase of data generated by information and communication technologies.
   • In recent years, the massive increase of data has become widespread in many fields of study due to the increase of technological devices, which have led to a significant increase in the volume of available data, however, having a large amount of data does not add value. The true value of data lies in its analysis and interpretation. With the passage of time, significant technological advances were made in hardware, although the improvement of computers allows with traditional techniques to load and process more data, they were not enough to index and cope with the massive increase in data, consequently, it was necessary an evolution of technology based on software.

2. Big Data Implication

   • Economic
     • Creation of new business models as they seek ways to manage large volumes of data.
   • Social
     • There is an exponential growth of data in many areas of everyday life such as the increase in the number of internet-connected devices, constant use of social networks, and the internet of things. It should be noted that the vast amount of data is open and accessible.
     • It should be noted that the vast amount of data is open and accessible.
     • Exploited by users or institutions worldwide.
   • Technological
     • Emergence of new techniques and data processing technologies.
   • Scientific
     • Requirements for new data models to facilitate the insertion, querying, and processing of any type and structure of data, as well as processing speed.

3. Main definitions of Big Data

   • Volume
     • Scale of Data
       • It's estimated that 2.5 quintillion Bytes of date are created each day.
   • Velocity
     • Analysis of streaming data
       • Modern car have close to 100 sensor hat monitor items such as fuel level and tire pressure.
   • Variety
     • Different form of data
       • 400 Million tweets are sent per day about 200 million monthly active users.
   • Veracity
     • Uncertainty of data
       • 1 in 3 business leaders don't trust the information they use to make decisions.

4. Big Data motivations

   • The systems focus on finding which aspects are related to each other and not merely by chance, thus enabling predictions to be made.
   • Data Exploitation: Make the most of the large amount of data they generate to obtain valuable information Improve decision making.
   • Optimize processes: Identify market trends and opportunities. Offer better products and services to customers.
   • Competitiveness: Gain competitive advantages through data analysis. Anticipate market demands. Develop marketing strategies.
   • Innovation: Enables the development of new technologies, tools and business models to solve complex problems and create value in new ways.
   • Efficiency and Productivity: Identify areas for improvement in your internal processes. Optimize resource allocation and reduce operating costs.