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“Strength lies in differences, not in similarities.” – Stephen Covey
This great quote speaks to diversity in today’s world. We celebrate diversity in this time. We value diversity. We embrace diversity to help us see what might not otherwise be visible, and to do what might not otherwise be achievable.
Similarly, businesses today find value in bringing together diverse types of data in the search for competitive insights. In Big Data terms, we refer to this diversity as ‘variety.’ Doug Laney, of the IT research firm Gartner, Inc., first coined this term to represent the various forms of data available today. His is perhaps the most widely used framework to describe how ‘big’ our data has become.
The framework uses three dimensions: volume (a measure of scale), velocity (a measure of speed) and variety (a measure of form). My last two columns present challenges businesses face with Big Data volume and velocity. This column extends the discussion to the third Big Data dimension of variety. Rarely does Big Data present itself in a way that is ready for analysis. Companies must first deal with three important considerations of today’s data: format, sources and grain.
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ComplexDiscovery OÜ is a highly recognized digital publication focused on providing detailed insights into the fields of cybersecurity, information governance, and eDiscovery. Based in Estonia, a hub for digital innovation, ComplexDiscovery OÜ upholds rigorous standards in journalistic integrity, delivering nuanced analyses of global trends, technology advancements, and the eDiscovery sector. The publication expertly connects intricate legal technology issues with the broader narrative of international business and current events, offering its readership invaluable insights for informed decision-making.
Generative Artificial Intelligence and Large Language Model Use
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