Managing data across the enterprise- How semantic web is changing the game

Most often enterprises struggle with siloed data. It's no surprise that integration of data across enterprise is a nightmare. PWC technology report provides some interesting perspective on how semantic web can make it real and ensure it can be done easier than ever before.

Here are some interesting facts contained in the report:

How is semantic web a game changer for data integration?

The disparate data feed into a mashup—a Web application with highly configurable data display capabilities—that updates each time you add a new store site or remove an old one. Other data in the mashup arerefreshed whenever the original sources are updated. By combining various data, regardless of their formator source, you have a wide range of possibilities forgreater insight and context.

The challenges with traditional data integration vs semantic web:

Generally enterprises don't make the best use of their data.

Given the disparate systems and multitude of vintage of technologies( old and new), it is always very difficult for business managers to use multiple source of data for decisions.



Getting internal and external to handshake with each other can help trigger power decisioning within organizations



.....empower your business users...

with exploration tools that they could use with existing internal data and with external data of their choosing. These tools would let them find the best business cases and make immediate use of the Linked Data technologies at a low cost to IT, since most of these tools are reasonably priced.

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Innovating GE way - Go back to School

Business Week reports:

It's a first, however, for General Electric's health-care unit, which sells $15 billion a year worth of clunky X-ray machines, CAT-scan machines, and ultrasound testing equipment. The health-care division has long been a technology innovator. But it has historically tried to differentiate its products by getting better and faster readings from its instruments—"feeds and speeds" as Lou Lenzi, the general manager of global design at GE Healthcare, puts it. So turning to art school students for ideas is a significant departure.

GE wants to make medical tests easier on both the patients and the operators of the equipment, which means focusing on the human side of the equation, from ergonomics to emotions. How, for instance, could a traditionally monstrous CAT scan machine be designed to seem less ominous to patients already distressed by their medical condition? How could a machine be easier for the technician to use?

"We're looking beyond the hardware. We're looking at the patient's journey."( says Lawrence Murphy, the health-care unit's chief designer (My emphasis)).

Improved Experience

There were other forces at work, too. One of GE Chief Executive Officer Jeffrey Immelt's initiatives has been to call on employees to "Go Big" by targeting large markets and ideas that might pay off in outsized ways. With that in mind, the health-care designers asked the Art Center students to look at how the company's services might be delivered in developing nations 20 years from now.

Making search customer-centric

Alex Iskold has a great post on Read/Write web on how search needs to get a lot more customer-focussed. The key take-out for me from the post is :

  • The 'simplicity of thinking' one needs to have when developing products or services.
  • It's about analysing 'customer interactions' and customer behaviour' first and then applying them to products or technologies.
  • It's the easy usability of the product or service that will determine acceptance and adoption.

Alex writes:

What is perfect search?

It is interesting to ask: What do we expect when we enter a term into a search box? Ideally, we'd like to get the perfect answer right away. Often, we have an idea what that perfect answer should be, and when computer does not get it for us we are disappointed. But are we being reasonable? Can we expect the "perfect" answer all the time?

Consider for example, our interactions with an Information clerk at the mall. When we ask for a location of a store, she may or may not give us the "perfect" answer. She might not know where this store is, she might not understand us or we may not understand what she said. So for many reasons we may not get the "perfect" answer right away.

What is qualitatively different between our experience with the Information clerk vs. a search engine is that with the clerk we have a dialog. When she does not understand what we asked, she has a chance, to say Excuse me, what do you mean?. Google does not do that, it just gives us the results. If we do not like the answer we have to start from scratch.

The problem is that human interactions are fundamentally iterative, while our interactions with computers are mostly stateless. Perhaps we could get to the perfect search results if we could have a dialog with the computer? Clustering technologies, particularly the one offered by Clusty, give computer a chance to clarify: Excuse me, when you searched for Alex Iskold, did you mean to look for Read/Write Web or AdaptiveBlue or perhaps you where looking for static analysis tools that Alex worked on while at IBM?.