Data volumes are exploding, with a staggering 90% of the world’s data being generated in the last two years alone. Discoverable data is getting its tentacles into more sources and types than ever before—mobile data, project management applications, collaboration tools, the list goes on and on. But as data volumes grow more complex, it’s difficult to reveal insights into the data and significant relationships between different classes of data. There is also a significant cost question to consider.
When handling large discovery projects, it’s important to have the right tools to get insights into the structure of a data set. Proprietary data visualization tools such as Everlaw can generate interactive visualizations from any set of documents and provide key insights into document metadata, contents, formats, dates, review activity, and predicted relevance. This enables early exploration of a document corpus by generating interactive, customizable visualizations from any set of documents, and by drilling down into data sets using the file path explorer.
With data visualization tools, it’s possible to:
Generate interactive visualizations from any set of documents that provide key insights into document dates, metadata, primary languages, contents, formats, review activity, and predicted relevance
Dig deeper into metadata, making it easy to drill down into the underlying file structure of documents in a data set
Explore the relationships between documents at a glance without the need to review individual documents or conduct a predetermined search
Leverage predictive coding data in comparison with other file attributes, making it easy to identify a broad class of relevant documents that might be missed by contextual and date filters
Perform quality control on productions and improve review accuracy
Join us for an interactive webinar exploring 3 use cases of data visualization that can reduce costs and save time in ediscovery.