First, Firster, Firstest: Three lessons from history on information overload
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The document discusses historical lessons on information overload and the evolution of data management, emphasizing that despite advancements, old challenges persist. It contrasts different classification systems and the trade-offs between top-down and bottom-up approaches in technology development. The conclusion suggests a need for pragmatic solutions and rethinking the future of data management beyond simplistic binaries like SQL vs NoSQL.
First, Firster, Firstest: Three lessons from history on information overload
- 1. First, Firster, Firstest Three lessons from history on information overload and technology Strata Conference September, 2011 Mark R. Madsen http://ThirdNature.net
- 2. Sivowitch’s Law of Firsts “Whenever you prove who was first, the harder you look you will find someone else who was more first. And if you persist in your efforts you find that the person whom you thought was first was third.” - Eliot Sivowitch Page 2
- 3. "Those who cannot remember the past are condemned to repeat it.” George Santayana If there’s one lesson we can take from history, It’s that nobody learns any lessons from history.
- 5. You keep using that word. I do not think it means what you think it means.
- 6. Good conceptual model, bad implementation The relational database is the franchise technology for storing and retrieving data, but… 1. Single, static schema model 2. No rich typing system 3. Limited API in atomic SQL statement syntax
- 9. “There is nothing new under the sun but there are lots of old things we don't know.” Ambrose Bierce
- 11. The Elizabethan Era Automated printing. Information explosion: ▪ 8M books in 1500 ▪ 200M by 1600 ▪ Commoditization Data management tech: ▪ Perfect copies ▪ Indices ▪ Topical catalogs ▪ First real encyclopedia ▪ Font standardization
- 16. Buffon Bottom up orientation Flexible structure Explanatory, descriptive Faceted classification
- 17. Linnaeus Top down orientation Static structure Descriptive rather than explanatory Taxonomic classification
- 21. vs vs
- 23. Charles Ammi Cutter Cutter Expansive Classification System (~1882) Bottom up orientation More flexible structure Explanatory, descriptive
- 24. Melvil Dewey Dewey Decimal System Top down orientation Static structure Descriptive rather than explanatory
- 25. vs
- 26. Every technology is a tradeoff between something History is always the same: ▪ Top down vs. bottom up ▪ Authority vs. anarchy ▪ Bureaucracy vs. autonomy ▪ Control vs. creativity ▪ Hierarchy vs. network ▪ Power vs. ease ▪ Dynamic vs. static In every choice, something is lost when something is gained.
- 27. So why did Linnaeus and Dewey win? Good enough wins the day It wasn’t solving the problem you thought it was.
- 28. What lesson might we apply from this? Ok, it’s not You write a Did you So how do It’s not a a database distributed just tell me I query the database, How do I mapreduce to go to database? it’s a key- query it? function in hell? I believe I value erlang. did, Bob. store! Perhaps you should think about pragmatism a little bit.
- 29. Dealing with data in the industrial era Paul Otlet at his desk
- 34. The Computer & Internet Were Invented in 1934 Otlet’s future vision: ▪ Technological developments will improve the ability to manage information ▪ Current technologies can be integrated to provide individual discovery, access and collaboration
- 35. The Mundaneum Worked, For a While Two primary flaws of the Mundaneum: ▪ Static, top‐down classification system ▪ Loading could not keep up with data production rates Sounds familiar
- 36. Information Management Through Human History New technology development creates New methods to cope creates New information scale and availability creates…
- 37. Big Data
- 38. You keep using that word. I do not think it means what you think it means.
- 39. Big data? Unstructured data isn’t really unstructured. The problem is that this data is unmodeled.
- 40. The future of data is the relational database SQL noSQL
- 41. The future of data is the relational database SQL noSQL
- 42. The false dichotomy can be removed by technology Code defines what’s possible now - maybe it’s time to recode
- 43. Conclusion
- 44. CC Image Attributions Thanks to the people who supplied the creative commons licensed images used in this presentation: manuscript_page.jpg ‐ http://www.flickr.com/photos/calliope/306564541/ manuscript_illum.jpg ‐ http://www.flickr.com/photos/diorama_sky/2975796332 bookshelf by spectrum.jpg ‐ http://flickr.com/photos/santos/1704875109/ moose.jpg ‐ http://www.flickr.com/photos/stephenandjes/4286949510/ Vatican library ‐ http://www.flickr.com/photos/paullew/1550844955 Copyright or unknown Little girl and fire – Dave Roth Procrastinate – http://www.cracked.com Fault tolerance ‐ http://browsertoolkit.com/fault‐tolerance.png
- 45. About the Presenter Mark Madsen is president of Third Nature, a technology research and consulting firm focused on business intelligence, analytics and information management. Mark is an award-winning author, architect and former CTO whose work has been featured in numerous industry publications. During his career Mark received awards from the American Productivity & Quality Center, TDWI, Computerworld and the Smithsonian Institute. He is an international speaker, contributing editor at Intelligent Enterprise, and manages the open source channel at the Business Intelligence Network. For more information or to contact Mark, visit http://ThirdNature.net.
- 46. About Third Nature Third Nature is a research and consulting firm focused on new and emerging technology and practices in business intelligence, data integration and information management. If your question is related to BI, open source, web 2.0 or data integration then you‘re at the right place. Our goal is to help companies take advantage of information-driven management practices and applications. We offer education, consulting and research services to support business and IT organizations as well as technology vendors. We fill the gap between what the industry analyst firms cover and what IT needs. We specialize in product and technology analysis, so we look at emerging technologies and markets, evaluating the products rather than vendor market positions.