I had a call with a Fortune 100 IT team that is looking at using semantic technology as an alternative to the Data Warehouse.  This is my favorite kind of conversation, since I firmly believe the traditional data warehouse is dead but just doesn’t know it yet.

This is the situation the IT team explained:

We need to aggregate information and present it to the user, so we build a warehouse.  We spend all this time building and designing the warehouse, and when it’s done they need something else.  Unfortunately, it’s not so easy to modify a warehouse once it’s running, so we build another one.  And then another.  The cycle has been repeating itself for years and is not sustainable.

The alternative to warehousing is Data Virtualization (EII, Data Federation…lots of terms for it)…or, at least that’s what they, and many others, see!  Essentially, they have been burned by years of working with an inflexible technology, so are looking to dump the approach all together.

I get this.  If a Durian is the only fruit you’ve ever smelled, you’d think all fruit were really stinky.

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SemTechBiz is Less Than 2 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !

What’s the link between the trends of more and more objects and even commercial transactions on the web being described in a machine-readable, semantic format and the endless streaming of all that data? Revenue-funded startup First Retail, whose principals Anne Jude Hunt and Simon G. Handley will be speaking at the upcoming Semantic Technology Conference in June, thinks the answer is semantic ETL.

Extract, transform, load (ETL) is a widely known concept in the well-charted terrain of the IT world. That’s about transforming a bunch of heterogeneous data to unify it within a data warehouse and get some use out of it.

Semantic ETL, says Hunt, is brought on by the fact that today people want to deal with the growing loads of streaming data while it’s streaming and that “people want intelligent data, machine-readable tags,[they want] to slice and dice it for BI in lots of different ways, so the  traditional data warehouse and relational database approach is just not working for people.” Cleansed and integrated semantic data loaded into distributed, scalable triple stores can come to the rescue.

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Photo Credits: Apple – FlickR/muffet ; Food Pyramid – FlickR/teacher_caroline_acsp

[Editor's Note: This article is intended to complement the post, "I’ve got a Federated Bridge to Sell You (A Defense of the Warehouse)" by Rob Gonzalez (Cambridge Semantics). Here, Michael Lang, CEO & Founder of Revelytix, weighs in on the degree to which federating information using semantic technology could compete with the capabilities delivered by data warehouses.]

The term “federation” is used often in the IT domain, but I have never seen it precisely defined, so here goes: A federation is a collection of entities that act according to a set of policies such that all of the entities interoperate and integrate with each other, and as a collection it is viewed as a single entity. Of course this definition is a description of the United States of America (which is a federation) – the road systems are integrated and interoperable, so are the legal systems of the states; and it could be applied equally well to the IT infrastructure of any large enterprise or the World Wide Web (emphasis on could), if we put the right pieces in place to make an IT infrastructure a federation. Read more

[Editor’s Note: At the Semantic Web Summit conference in Boston in November, a discussion arose around Federated Data vs. Data Warehousing.  Rob Gonzalez of Cambridge Semantics raised some very interesting points that I asked him to expand on in the post below.  And whether you agree or disagree, we want to hear from you.

The Semantic Web dream of data federation is awesome.  You type in a query, and magical, intelligent agents scurry all over the datasphere, bringing back information to give you a complete, up-to-date, correct answer to your question.  No need for a messy, time-consuming datamart project!  What’s not to love, right?

Eric asked me to write this piece, and so I find myself in the unenviable position of having to tell you, dear reader and Semantic Web fan, that there is no Santa Claus (of data federation).  I’d like to make a case for the continued need for data consolidation in datamarts—yes, even in the Semantic Web-world—to gain real value from your enterprise data. Read more

This is the second of a two-part series discussing how Semantic Web Technology can enable Dynamic Business Applications in the enterprise. Read Part 1 of the article here.

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Part  1 – Understanding The Semantic Value Proposition

The term “Semantic Web” has developed some interesting yet confusing connotations since it was first introduced in the early 2000’s. Those misconceptions include but are not limited to:

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Executive Summary

The current information management tools and techniques have not kept pace with the dramatic growth of data within the enterprise. Much of this new data is represented in an unstructured or semi-structured format. The volume of the data makes it unmanageable by humans and the structure of the data makes it unavailable for machine processing. This has created a situation where information is now hidden or lost within the enterprise. This lost information has a significant business impact in the form of unmanaged risk and lost opportunities for revenue or savings.

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In many ways the practice of information technology has changed little over the past 30 years or so. It may not seem so on first appearance – but the premises upon which our current technologies are still operating are largely based on philosophical constructs that date back 30 years or more.

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