Big data can be a sensitive topic when lawsuits or regulators come knocking—especially if the potential legal risks have not thoroughly been considered by companies early on as they put in place big data systems and then rely upon its associated analysis. Thus it’s important to bring in the lawyers together with the technologists early, though this is not always easy to do. Big data from a legal perspective includes consumer privacy and international data transfer (cross-border) issues, but more risky is the potential exposure of using that data in the normal course and maintaining the underlying raw data and analyses (e.g., trending reports). For example, one question raised is about those parts of an organization’s big data that may be protected by a legal privilege.
Some examples of big data usage in the market that carry critical legal implications and ramifications and which have their own tough questions include:
- Determining customer trends to identify new products and markets
- Finding combinations of proteins and other biological components to identify and cure diseases
- Using social-networking data (e.g., Twitter) to predict financial market movements
- Consumer level support for finding better deals, products, or info (e.g., Amazon just-like-this, or LinkedIn people-you-may-know functions)
- Using satellite and other geo-related imagery and data to determine movement of goods across shipping lanes and to spot trends in global manufacturing/distribution
- Corporate reputation management by following social media and other internet-based mentions, and comparing those with internal customer trend data
- Use by government and others to determine voting possibilities and accuracy for demographic-related issues
The Legal Risks of Big Data
With respect to the legal risks involved, what’s good for the goose is good for the gander. That is, it’s important to remember that use of big data by a company may open the door for discovery by opposing litigants, government regulators, and other legal adversaries.Technical limitations of identifying, storing, searching, and producing raw data underlying big data analysis may not guard against discovery, and being forced to produce raw data underlying the big data analysis used by the organization to make important (possibly, trade secret classified) decisions can be potentially dangerous for a company—especially as that data may end up in the hands of competitors. Thus, an organization should perform a legal/risk evaluation before any analysis using big data is formulated, used, or published.
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