how the data we generate is used
Posted: Thu Jan 23, 2025 7:06 am
This term, or its Spanish equivalent “big data”, refers to a volume of data so complex that it cannot be processed with any type of traditional software or hardware. In itself, it is a neutral concept , as it can also refer to an unmanageable amount of data from research. However, given that the data collected may be of a personal nature (communication or consumption habits of users), the term has ended up acquiring a negative tone. Its detractors see the collection of data, and especially its evaluation, as a clear attack on personal rights.
How big is big data?
The concept of big data does not refer to a specific amount of data, as there is no defined limit beyond which massive data is considered big data. In practice, the term is synonymous with a volume of data that cannot be measured in gigabytes.
How is big data generated?
The volume of data has grown exponentially: the amount of data collected by realtor email database humanity from the beginning of its history until 2002 was generated in 2014 within ten minutes. According to forecasts, this mountain of data will continue to grow, doubling every two years. This tidal wave of data is a consequence of the general digitalisation in all areas of daily life and comes from sources such as:
Internet connection from mobile
Social networks
Geolocation
Cloud computing
Measurement of vital data
Consumption of audiovisual media
Big data is not just about the data itself, but also about its analysis and use . This evaluation process attempts to find patterns and connections in order to put it into context correctly. The challenge is not only the sheer volume of data, but also its speed and variety (the three “v”s of big data), since these are constantly being fed into an unstructured archive and must ideally be recorded, stored and processed in real time . To read them correctly and be able to connect them, a sophisticated data infrastructure is required.
How can I work with big data?
Big data is responsible for the emergence of new technical requirements for software. To analyse this data, special frameworks (digital infrastructures) are required , whose main function is to process as many data sets as possible and import them quickly. In addition, this software must make data available to the user in real time and simultaneously respond to multiple database requests.
Hadoop is a well-known open source solution for this purpose, although its extremely complex implementation often requires the support of experts, the so-called data scientists . However, to enter the world of big data, cloud solutions are a very good option.
How big is big data?
The concept of big data does not refer to a specific amount of data, as there is no defined limit beyond which massive data is considered big data. In practice, the term is synonymous with a volume of data that cannot be measured in gigabytes.
How is big data generated?
The volume of data has grown exponentially: the amount of data collected by realtor email database humanity from the beginning of its history until 2002 was generated in 2014 within ten minutes. According to forecasts, this mountain of data will continue to grow, doubling every two years. This tidal wave of data is a consequence of the general digitalisation in all areas of daily life and comes from sources such as:
Internet connection from mobile
Social networks
Geolocation
Cloud computing
Measurement of vital data
Consumption of audiovisual media
Big data is not just about the data itself, but also about its analysis and use . This evaluation process attempts to find patterns and connections in order to put it into context correctly. The challenge is not only the sheer volume of data, but also its speed and variety (the three “v”s of big data), since these are constantly being fed into an unstructured archive and must ideally be recorded, stored and processed in real time . To read them correctly and be able to connect them, a sophisticated data infrastructure is required.
How can I work with big data?
Big data is responsible for the emergence of new technical requirements for software. To analyse this data, special frameworks (digital infrastructures) are required , whose main function is to process as many data sets as possible and import them quickly. In addition, this software must make data available to the user in real time and simultaneously respond to multiple database requests.
Hadoop is a well-known open source solution for this purpose, although its extremely complex implementation often requires the support of experts, the so-called data scientists . However, to enter the world of big data, cloud solutions are a very good option.