Fri. Apr 19th, 2024
Master-Data-Management
ARCHIVED CONTENT
You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.
 

pablo-56-BigData

By Jelani Harper

Initially, Master Data Management (MDM) systems and the content they contain may seem counterintuitive or even diametrically opposed to Big Data systems. Some of the considerable differences between Master Data and Big Data include:

  • Volume: Comparatively, Master Data sets are much smaller than those for Big Data. One of the pivotal attractions for Big Data is that it encompasses enormous volumes; a person could argue that one of the points of attraction for Master Data is the opposite.
  • Structure: Master Data tends to contain structured data, while the majority of Big Data is either unstructured or semi-structured.
  • Relationship to the enterprise: Typically, MDM systems contain an organization’s most trusted data, which tends to be internal, while Big Data platforms quarter enormous amounts of external data from any number of cloud, social media, mobile, and other sources beyond the enterprise’s firewall. As indicated by Gartner, “MDM is more oriented around internal, enterprise-centric data; in an environment the organization feels it has a chance to effect change, and so formal information governance.”

Despite these differences, there are numerous ways in which Master Data Management can enhance Big Data applications,

 

Have a Request?

If you have information or offering requests that you would like to ask us about, please let us know, and we will make our response to you a priority.

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.

For the latest in law, technology, and business, visit ComplexDiscovery.com.

 

Generative Artificial Intelligence and Large Language Model Use

ComplexDiscovery OÜ recognizes the value of GAI and LLM tools in streamlining content creation processes and enhancing the overall quality of its research, writing, and editing efforts. To this end, ComplexDiscovery OÜ regularly employs GAI tools, including ChatGPT, Claude, Midjourney, and DALL-E, to assist, augment, and accelerate the development and publication of both new and revised content in posts and pages published (initiated in late 2022).

ComplexDiscovery also provides a ChatGPT-powered AI article assistant for its users. This feature leverages LLM capabilities to generate relevant and valuable insights related to specific page and post content published on ComplexDiscovery.com. By offering this AI-driven service, ComplexDiscovery OÜ aims to create a more interactive and engaging experience for its users, while highlighting the importance of responsible and ethical use of GAI and LLM technologies.