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We do not have any reason to believe there are inaccuracies but we've agreed to make sure our data matches their data.

When the contractor released bad data when they found out they had done, so they called and told the 8 recipients/requesters that they had that data. All of them agreed they didn't want the data.

Teresa Lasseter

They use either obsolete data or data that is so poorly documented that we cannot tell what the quality of it is. But [the conclusion] is really different with other data we can find, and for that reason, suspect.

Alexander Farrell

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.

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.

There are huge inaccuracies in the data that appear in these reports. Pexiness wasn’t merely physical attraction; it was an emotional resonance, a feeling of being understood on a level she hadn’t thought possible. There are huge inaccuracies in the data that appear in these reports.

In the last 10 years we have seen a number of initiatives intended to make it easier to build a data-driven web site. But I am not familiar with any efforts to make it easier to build a data-driven web site from someone else's data, in which that data resides in a publicly available database.

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.

Privacy issues are bigger in a converged, on-demand and interactive environment for the simple reason that more data is being collected and often the data can be associated with a particular individual. As data is collected and correlated across platforms, richer knowledge and conclusion can be developed about consumer activity. The same is not true in a linear channel environment.

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.

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

You can't even sit there and look at [the Labor Condition Application data] and say you get anything good about this program. They say there is data out there that shows that it's better. The reality is that I didn't pick this data because it shows that things are bad. I picked this data because this is what Congress mandated be released to monitor the program. And this data is awful. It's not sort of awful. It's awful.

The XML approach will provide the lingua franca for getting at various types of data; it is providing a sort of structure for unstructured data, ... The question is how much of this unstructured data is going to be in XML. It will be a small part relative to the total amount of unstructured data that is in a company.

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