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Big data and its role in digital forensics

Big data is getting all the hype and it is generally linked with personal data which is collected by large and medium scale enterprises. The use of big data analytics is underutilized, but it is now finding its way into digital and mobile forensics. There are four main pillars of big data including volume, variety, velocity, and value. Let’s talk about it in details: 

  • Volume: It is the amount of data collected from different devices. 
  • Variety: The wide range of files or data, which is present in the medium. 
  • Velocity: The amount of time required to acquire and process the data. 
  • Value: The value of the actual intelligence collected when the data is processed accurately.

Challenges in digital forensics: 

  • Storage: There is no proper size to refer to big data. Its classification is complex than just numbers. Although 1 terabyte can be accepted as a dataset that qualifies as big data. As per International Data Corporation, every person online will create an average of 1.7 megabytes of new data every second by 2020 and only 37% of the big data can be analyzed. 
  • Structured vs. unstructured data processing: Structured data have defined known structures such as numbers, dates, groups of words, and so on. This data can be regularly tapped into during an investigation. The unstructured data is information that does not have a pre-defined data model or cannot be structured properly. 
  • Intelligence prediction: To generate tangible intelligence from big data, and intelligence extraction process is used to examine the data. The main aim of the phases is to put structured, unstructured as well as semi-structured data in a tangible format. 


  • Training: It is important to understand how to process big data and the best method of understanding the knowledge is by applying to investigate and extraction techniques. 
  • Ecosystem approach: Ecosystems are utilized to enable professing lifecycle of big data. The systems can typically start with identifying the media containing the data and identifying the extraction profile required for each type. 
  • Practical application: Examiners who are concerned with the accurate processing the big data should combine customized vendor solutions, vendor-neutral software, and their extraction knowledge to ensure digesting solutions. 

Bottom Line Big data can provide different benefits to forensic examiners. The examiners can utilize advanced search techniques built into the software to address different items which are available in the mails or search history. These techniques present instant results to an examiner when they search for different information. The analysis techniques assist the law enforcement agencies to understand the behavioral pattern or identify a suspect who has been involved in d