If You Have Too Much Data, then "Good Enough" Is Good Enough: In today’s humongous database systems, clarity may be relaxed, but business needs can still be met.

Abstract

Classic database systems offer crisp answers for a relatively small amount of data. These systems hold their data in one or a relatively small number of computers. With a tightly defined schema and transactional consistency, the results returned from queries are crisp and accurate. New systems have humongous amounts of data content, change rates, and querying rates and take lots of computers to hold and process. The data quality and meaning are fuzzy. The schema, if present, is likely to vary across the data. The origin of the data may be suspect, and its staleness may vary.

References

1. Baker, J. Bond, C., Corbett, J. C., Furman, JJ, Khorlin, A., Larson, J., Léon, J. M., Li, Y., Lloyd, A., Yushprakh, V. Megastore: providing scalable, highly available storage for interactive services. In Proceedings of Conference on Innovative Data Systems Research (Asilomar, CA, 2011); www.cidrdb.org/cidr2011/Papers/CIDR11_Paper32.pdf.
2. Helland, P. Data on the outside versus data on the inside. CIDR 2005; www.cidrdb.org/cidr2005/papers/P12.pdf.
3. Helland, P. Normalization is for sissies. Conference on Innovative Data Systems Research (2009); http://blogs.msdn.com/b/pathelland/archive/2007/07/23/normalization-is-for-sissies.aspx.
4. Microsoft Developer Network. SQL Azure (2011); http://msdn.microsoft.com/en-us/windowsazure/sqlazure/default.aspx.
5. Wikipedia. Mulligan stew; http://en.wikipedia.org/wiki/Mulligan_stew_(food).
6. Wikipedia. Werner Heisenberg; http://en.wikipedia.org/wiki/Werner_Heisenberg.