Open Source to E-discovery
As a data scientist who is working in E-discovery industry, I am glad to be able to use many good tools to work with E-discovery data, i.e. Nuix for processing, Relativity for review and some analytics, and so on. However, the limitation for any hard-coded software is they do not always work well when data is messy and unorganized. Coupled with the high license fees and server fees, those tools are not always a good option. So, is there anything free that you can rely on to perform all the core functionalities that those big tools provide? Well, the answer is yes and no. Yes, there are numerous open source tools that can do what you are looking for, and No, you still need to pay money for hiring a data scientist but not pay money for software. To demonstrate an open source approach to E-discovery, I decide to start writing blogs about this topic. When it comes to data, Python is hands down a very good option. (The other equivalent is R). Python has a very complete and robust standar...