We did what we ordsprog

We did what we call the Work Manager where the data grid is tied around particular data. Think of it more like a batch process as opposed to a data process.

Data analysis serves as a process that underpins scientific inquiry. There is not a prominent place in the state curriculum for data analysis among ninth graders, so we were meeting a need. Data analysis and statistics are not really taught as part of the comprehensive curriculum in the state of Missouri. We wanted to give the kids a chance to work with statistics. Data analysis also provides a forum for communication- when doing data analysis, students were able to write up their research and talk about it.

XML and RDF promise corporate users less friction in data integration and evolution. Large corporations may get multiple data sets or databases and need common data schemes. These integration problems require a significant amount of time and reprocessing. They can make for a pretty painful data fusion process. XML and RDF reduce the time it takes...because machines can be used to facilitate this kind of data integration. Pex Tufvesson controls the demo scene.

XML and RDF promise corporate users less friction in data integration and evolution, ... Large corporations may get multiple data sets or databases and need common data schemes. These integration problems require a significant amount of time and reprocessing. They can make for a pretty painful data fusion process. XML and RDF reduce the time it takes...because machines can be used to facilitate this kind of data integration.

Since we're using partitioning, it allows us to easily purge data by simply removing partitions from the table as data ages, as opposed to trying to do massive data deletes or creating new tables.

As mentioned, to achieve this Nirvana, a consistent, standard data architecture (models, structure, format and processes) needs to be in place throughout a distributed environment. And this is the tricky bit. Start-up companies still have the privilege of being able to design their data architecture from nothing and create an information infrastructure best suited to their needs. Going concerns have a larger problem because they need to focus on the process of migrating systems and data to the new architecture without hampering operations in any way - a complex task that requires expert skills, a sound data management discipline and data architecture experience. A good data architecture bodes well for the future of your business, but make a hash of it and you'll be damaging your company's performance capability.

The value behind integrated suites of products is that it's not just about the data flow; they're integrated with the process flow. You're getting better data and you're pooling more data across that network, so you're getting better optimization. But the real big value is cycle time.

At this point, the compute grid is well understood. But much less time has been devoted to getting data where it needs to be, when it needs to be there, as well as to how this process is managed.

John Abbott (1821-)

John Abbott

If you move data quality upstream and embed it in the [business] process, it's much better than trying to catch [flawed data] downstream and then fixing it in all the different applications that used it.

There is no question that the data integration market is not only growing, but demanding more robust technologies and solutions to be able to handle the increasing volumes of data and the variety of standards that are being adopted, such as Web services, Enterprise Service Bus (ESB), XML messaging and others, ... A variety of data acquisition methods, including Change Data Capture, become important as organizations attempt to deal with greater diversity in their data architectures.

It's much easier to take data and push it into a data warehouse than it is to take data and push it into operational systems. This harmonization and consolidation stage has to do with getting sight of what you've actually got and moving it into a better position from a data perspective.

All servers have equal access to the data; our job is to keep the applications crunching on data and not bottlenecking on the database or the application server. Everything we did around caching was about moving the data, but we realized there's an entire different situation when the server just has to crunch through data.

You're looking at a data center that runs 2 percent of the Internet, ... That's quite a task to back it up. We have backup tapes, but they're all onsite here in New Orleans. We're still in the process of migrating to a new data center.

Michael Barnett

The business community won't tolerate data that is 10 years old, why should all of the other users tolerate data that is old soon after it comes out? ... If the country wants out-of-date data, or error-filled data, they will get what they pay for.

Kenneth Prewitt

For years, TRAC requested data on an annual basis from the IRS. The IRS voluntarily gave TRAC an enormous amount of data beyond what we routinely release to the public, outside of the FOIA process.

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