Big Data & Business Intelligence

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Sarah Sutherland, Damien Riehl, Michael Sander, and Jae Um

Data collected and analyzed at scale can reveal information from which organizations can draw conclusions and make well-informed decisions. Big data and business intelligence are related but distinct fields, most often used by organizations to analyze behavior and predict outcomes.

Big data implies huge datasets (terabytes of data) with relatively low information density. In other words, you’ve got just a few points of data about millions or billions or trillions of things.

Business intelligence implies smaller datasets with relatively high density. In other words, you’ve got a lot of points of data about hundreds or thousands or millions of things—probably users or customers.

Big Data

Business Intelligence

While business intelligence might sound like the sort of thing only big companies can do, it can be available to organizations of all sizes. Some common examples include:

  • Website statistics software like Google Analytics, which can give you insights into the people who visit your website.
  • Marketing software like HubSpot, MailChimp, and Salesforce, which can give you even more information about people who visit your website, view your emails, and more.
  • Some practice/project management software is designed to aggregate data about clients and matters.

Starting in 2016, Clio began publishing its Legal Trends Report, which uses anonymized, aggregate data from Clio users, as well as external survey data, to deliver generalized insights into the legal industry.

Published on February 9th, 2021. Last updated on March 16th, 2021, by Sam Glover.