What Is Big Data?
The following article explains of big data in real time. The Internet is awash with data and new data is being generated every day at a very first rate. This state has lead to the development of a new subfield in the field of ICT-big data. The definition of big data varies considerably. In the field of big science, identifying big data is done by considering three factors; the velocity, volume, and variety of the data. This has lead to the generation of the 3V model that is used to identify big data.
Big data is, therefore, any structured, semi-structured or unstructured data that is generated at huge velocity, in large volumes and is of the wide variety that the traditional data management systems and techniques are not capable of handling. Traditionally data is usually managed by relational databases, which conducts an analysis of the data relying on schema and data quality. However, these traditional data analysis techniques are not powerful enough to process the petabytes and exabytes of data generated by the internet today. The term big data is thus used to describe this type of data.
The term big data has also been used to describe the field of processing and analyzing big data. Companies that send these services use the term in reference to this field and not just the volume of data that is involved.
CHARACTERISTICS OF BIG DATA
- Volume of the data
For data to be considered to be big data, it contains large amount to the tune of petabytes and exabytes. It should also create a problem in its management processing and analysis.
- Velocity of data
Big data is data that is generated at a fast rate. This poses a challenge of how it is stored and analyzed.
Big data vary considerably. The sources of this data vary and so does the structure of the data. It may be structured semi-structured or completely unstructured.
Big data is usually complex because of the multiple sources. Different sources lead to different data structures and different amounts.
This means that the data compromises big data varies in quality. Some data may be of high quality while others may be of poor and low quality.
Processing of Big Data
As mentioned earlier, traditionally used to handle data and it is not adequate enough. This has prompted the development of new data processing techniques and software. To process the large and high amount of data in real time using traditional relational databases is expensive and takes time. Data processing of big data relies on artificial intelligence and learning machines that run complex algorithms that analyze the aggravated raw data. All the data is aggregated to form a data lake in a network of connected servers.
Big data has proven to be useful. A large amount of data helps organizations for better decisions that are comprehensive. Data mining carried out on this lake of data is invaluable due to plenty of patterns that can be deduced from the data. So big data reveals the complexities and near picture of reality.