MODELING UNSTRUCTURED DATA:
Be prepared to analyze and design complex data requirements

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by Steve Hoberman download a PDF brochure Download Event Brochure

Description

As data requirements mature, as megabytes become cheaper, as CPU speed becomes faster, we as analysts and modelers will be faced with more complex requirements. Many of these requirements will depend on the efficient storage and retrieval of unstructured data. Merrill Lynch recently estimated that over 85% of all Business information exists as unstructured data. The sheer quantity and complexity of unstructured data opens up many new opportunities for the analyst and modeler. Imagine requirements such as:

  • Show me consumer feedback on my product from all Website discussion groups for the last six months
  • Show me all photographs taken of the fountains in Rome from the summers of 2002 through 2007
  • Show me all contracts which contain a particular liability clause

As with many areas of information technology however, there is ambiguity and confusion on the definitions and therefore the Business and information technology implications of unstructured data.

This seminar will clearly explain unstructured data as well as related concepts such as Ontologies and Taxonomies in a context that will help you identify new Business Intelligence opportunities and design efficiencies for your organizations. Through a combination of lecture and exercises, we will reinforce unstructured data concepts and challenges.Each participant will receive a copy of all presentation material and a copy of the book “Data Modeling Made Simple”, by Steve Hoberman.

What you will learn

  • Distinguish between structured, semi-structured, and unstructured data
  • Separate Content from Requirements
  • Build relational and dimensional models which leverage text tagging, Ontologies, and Taxonomies

Main Topics

  • The necessity of ‘Wayfinding’ in today’s rapidly changing Business Intelligence world
  • The need to expand our understanding of traditional modeling concepts such as Metadata, domains, and class words
  • The distinguishing factor between structured, semi-structured and unstructured data
  • The recurring dream every CEO and CIO share
  • The necessity to separate content from requirements
  • The challenges that unstructured data will surface
  • The expanded set of activities the analyst and modeler will perform in the next 2-5 years
  • The power of text tagging
  • The difference between a Taxonomy and an Ontology