Big data is a term that has been making all the headlines these days. It is basically a collection of large amounts of structured and unstructured data sets that existing database management software can’t handle.
The relationship between e-discovery and big data has become significant in the last few years with litigators identifying the benefits that big data analytics might have for speeding up the litigation process. This is the reason why most e-discovery practitioners are trying to develop new techniques and skills that can help them in managing and analyzing big data sets.
Challenges Involved in Handling Big Data with Existing E-discovery Tools
The following are some of the challenges that are encountered by litigators when trying to handle big data with the existing e-discovery tools.
- The sheer size and magnitude of big data.
- Inefficiency in the analysis of big data.
- Economic factors
The tools used by e-discovery practitioners nowadays mostly comprise of relational databases that are not equipped to handle the high volume of data, associated with big data. Moreover, the existing tools of e-discovery are not capable of efficiently analyzing and extracting the critical information from these huge data sets.
Economic factors are also among the challenges that are faced by litigators when dealing with a big data set during an e-discovery effort, as reviewing the large number of documents in the big data set will require a lot of money to be spent. It is because of these challenges that people are considering the need of development of new tools and methods for e-discovery that are capable of handling the sheer size and magnitude of big data in an efficient manner.
Solutions for Meeting these Challenges
The following are some of the solutions that have been suggested for addressing the above-mentioned challenges in the handling of big data.
- Use of computer assisted reviewing or predictive coding
- Parallel processing of data
- Utilization of new data mining and managing techniques
When handling big data sets during the phase of e-discovery the biggest challenge in front of litigators is that of reviewing the ultra high number of documents. This challenge can be effectively dealt with using computer-assisted reviewing that will make the task of the e-discovery practitioners a lot easier.
The use of parallel and grid processing is another solution that can help in the management of large data sets. This would help in dealing with the sheer size of data that is present in a big data set. Likewise, the development of new techniques for data mining have also been suggested as a possible solution for meeting the challenges that are associated with the processing of big data sets.
Thus, even though there are challenges involved in processing big data sets during an e-discovery effort, they are outweighed by the advantages and benefits that can be gained from the use of big data in the litigation process. An otherwise tedious, time consuming process can now be more automated, leading to efficiencies never before thought possible- a true breakthrough in the eDiscovery process.
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