What is Big Data?
Big data is a term that describes the large volume of data, structured and unstructured, that floods a company on a day-to-day basis. Big Data is a term used for a collection of large and complex data sets that is difficult to store and process using the available database management tools or traditional data processing applications. The challenge includes capturing, curing, storing, searching, sharing, transferring, analyzing and visualizing this data.
Types of Big Data
Classification is essential for the study of any issue. Then Big Data is broadly classified into three main types, which are-
By structured data, we mean data that can be processed, stored and retrieved in a fixed format. It refers to highly organized information that can be easily and perfectly stored and accessed from a database by simple search engine algorithms. For example, the table of employees in a database of the company will be structured according to the details of the employee, their positions, their salaries, etc., will be present in an organized manner.
Unstructured data refers to data that does not have any specific form or structure. This makes it very difficult and slow to process and analyze unstructured data. E-mail is an example of unstructured data.
Semi-structured data refers to data that contains the two formats mentioned above, that is, structured and unstructured data. To be precise, it refers to the data that, although they have not been classified in a specific repository (database), contain vital information or marks that segregate individual elements within the data.
Characteristics Of Big Data
The name Big Data itself is related to a size that is huge. The size of the data plays a crucial role in determining the value of the data. In addition, if a specific data can be considered as a Big Data or not, it depends on the volume of data. Therefore, ‘Volume’ is a feature that needs to be considered when dealing with Big Data.
Variety refers to heterogeneous sources and the nature of the data, both structured and unstructured. In the first days, spreadsheets and databases were the only sources of data considered by most applications. Currently, the data in the form of e-mails, photos, videos, monitoring devices, PDF, audio, etc. they are also being considered in the analysis applications. This variety of unstructured data presents certain problems for storage, mining and data analysis.
The term speed refers to the speed of data generation. The speed with which the data is generated and processed to meet the demands determines the real potential of the data. Big Data Velocity handles the speed at which data flows from sources such as business processes, application logs, networks and websites, social media, sensors, mobile devices, etc. The data flow is huge and continuous.
Applications of Big Data
Entertainment: Netflix and Amazon use Big Data to make shows and movie recommendations for their users.
Insurance: use Big Data to predict illnesses, accidents and price their products accordingly. about one gigabyte of data per second.
Education: Opting for technology powered by big data as a learning tool instead of traditional classroom methods, which improved student learning and helped the teacher to accompany
Cars: Rolls Royce adopted Big Data by installing hundreds of sensors in their engines and propulsion systems, which records every tiny detail of your operation. Changes in the real-time data are reported to the engineers who will decide the best course of action, such as maintenance programming or shipment of engineering equipment if the problem demands.
Government: A very interesting use of Big Data is in the field of politics to analyze patterns and influence the results of elections. Cambridge Analytica Ltd. is one of those organizations that fully impels the data to alter the behavior of the audience and plays an important role in the electoral process.