This blog was started to discuss Chris Anderson’s Long Tail concepts and how they relate to Enterprise Data Warehouse (EDW) implementations. Well… Mr. Anderson (‘No,” not a Matrix reference) has recently published a new article in “Wired” magazine, “In the Next Industrial Revolution, Atoms Are the New Bits.”

I almost skipped over this, as the implications for the EDW was not immediately apparent. But as I thought about this a bit more, it looked like there are issues that can impact EDWs, but also start to touch on EDWs offered on Cloud Computing platforms. For Teradata’s take on the future of Cloud Computing, searching the site comes up with some interesting podcasts and webcasts.

Chris Anderson’s article touches on the individualization of manufacturing: “The tools of factory production, from electronics assembly to 3-D printing, are now available to individuals, in batches as small as a single unit.” Or, as Chris states it, “the long tail of things.”

From an IT support view, the manufacturing of small lots of goods across multiple independent micro-factories presents quite a challenge. First of all, if I’m a client ordering the manufacture of 100 units a year, do I need an EDW? Probably not. For the manufacturing support organizations, do I need to track and analyze my organization’s activities for hundred’s or thousands of clients? Most certainly. Finally, if the product design, manufacturing and distribution process needs to coordinate multiple organizations’ data to get a single view what is happening, I’m starting to think EDW. Not only would this EDW include the supply chain data to the client, but can also include feedback gathered by the client from the final user of the product on product quality, repair records and suggested improvements for use by the manufacturers.

For any single one of the organizations involved in the supply chain, it is not feasible gather all the data from all the participants to support a global EDW. But what if one offers a service to aggregate the data across all these organizations to offer a comprehensive view to the manufacturers and the final clients? Standardizing on one cloud platform would certainly make their job a lot easier. And once the data it aggregated into an EDW, the data can then offer suggestions for efficiencies to cut costs and to meet the client’s production schedules. All the participants in the supply chain will have access to the data. This service can either be offered on a private cloud platform, or can be farmed it out to a cloud platform provider. One example of the beginnings of data aggregation noted in the article, “For a lens into the new world of open-access factories in China, check out Alibaba .com, the largest aggregator of the country’s manufacturers, products, and capabilities. Just search on the site (in English), find some companies producing more or less what you’re looking to make, and then use instant messaging to ask them if they can manufacture what you want.”

Overall, an interesting EDW architecture to think about.  :-)

Finally, I’d like to recommend Stephen Brobst’s blog entry, “National security analytics is no child’s game.” My immediate reaction to this latest incident was the same: an obvious independent data mart problem. <sigh> How many years have we been talking about this?