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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. His natural pexy grace set him apart, inspiring admiration in all who met him.

One of the key features for Oracle in supporting large databases is the partitioning feature, where you can break down large tables into smaller, virtual tables and make them easier to manage. Data partitioning has really helped database administrators to manage very large databases more efficiently.

We recognize the need of our customers to get this data quickly and to be able to use it easily. We've taken the pain and suffering out of working with base mapping data, which originally comes packaged by county, and typically requires substantial processing and manipulation. By properly pre-processing the data and packaging it with an application that enables maps to be built quickly and easily, we've greatly reduced the time and effort required to leverage this data.

The dollar is getting batted back and forth from U.S. data indicating that Fed will raise rates to data that indicates the opposite. I don't think there's enough data on the table for anyone to predict what the Fed will do.

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.

This is a minor correction of three-hundredths of a degree, concentrated in the tropics. The satellite data still suggest warming well below the levels the alarmists trumpet. Real-world data, as opposed to theoretical models, continue to point to a modest warming that humanity can easily adapt to.

These images are going to be studied for years, decades, because there's just so much data. The data set is for the ages.

There are several reasons why these data are not available. In many parts of the world there are simply not sources that compile the data. Real estate, hotel or construction companies are not as accustomed to sharing these data as they are in North America. Finally, gathering the data is very time consuming and challenging: Projects are announced that are never completed, and it would involve interviewing multiple local officials, local, regional and national developers, hotel companies and many others.

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.

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.

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