Beyond Big Data—Opportunities, Challenges, Solutions, Copenhagen, 12 Nov 2015 (link in Danish)

In this 2-hour session, Dr. Barry Devlin covers business considerations, architectural and technological aspects, and the broader ethical and economic issues surrounding the world beyond big data. With a draw for 3 copies of “Business unIntelligence”.

The creative use of big data, especially that from the Internet of Things, is transforming business models, empowering start-ups, and enhancing or destroying existing business value. Many proponents focus on marketing uses of big data, but most value—or disruption—will come from its daily application in novel and transformative ways. For IT, making the right architectural and technological choices is vital in designing and managing the automated environments big data should have and the Internet of Things will demand. Significant improvements in data management and governance will be needed. Furthermore, business and IT together must look at the broader ethical and economic issues raised by big data. Concerns around personal privacy, employment and social disruption must all be urgently addressed if individual businesses and society at large are to successfully navigate this data driven transformation of all aspects of business and technology.

In this session, Dr. Barry Devlin addresses:

  • Business considerations
    • Business use cases in marketing and beyond
    • A framework for understanding real usage patterns: the Simple Business Model
    • Data driven or information informed?
  • Architectural and technological approaches, evolution vs. revolution
    • Positioning data, information, knowledge and meaning
    • Context-setting information and the evolution of metadata
    • Governance and Data Warehouse Automation
    • Data Reservoirs and Lakes and how they compare to the Data Warehouse
    • Technology choices, focus areas for new tools, hype to avoid
  • Dealing with the broader issues around big data use
    • Implementing a big data strategy
    • Addressing the privacy deficit
    • The increasing economic impacts of algorithms and automation
    • Ethical use of big data