Additive manufacturing is the process of joining materials to make objects from 3D model data, usually layer upon layer.
As a result, they can do what-if analysis, model data, and run sophisticated data mining and forecasting algorithms that return answers within minutes, enabling them to fine-tune and refine their offers and service bundles to accurately reflect the needs of their subscribers.
Typically, these are motivated by a conspicuous success, a development program that was driven by the strength of beautiful molecular data, and the canonical example these days is PCSK9, a target which seems to feature an almost unprecedented alignment of human genetics, biomarker, and animal model data.
However, I think Data Vault is still very usable to model the data, to structure it, to deal with issues like cascading updates and to cope with the overall complexity.
Sageworks collects financial statements for private companies from accounting firms, banks and credit unions through its cooperative data model, aggregating the data at an approximate rate of 1, 000 statements a day, and analyzing the performance.
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By adopting a Big Data model, the analysis of massive data sets will create actionable information, eliminate blind spots where threats can lurk undetected and, ultimately, help to shrink our windows of vulnerability.
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Some sort of master data model is needed to make sense of all of this data.
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Through its cooperative data model, Sageworks collects financial statements for private companies from accounting firms, banks and credit unions, and aggregates the data at an approximate rate of 1, 000 statements a day.
Construction Sector DataThrough its cooperative data model, Sageworks collects financial statements for private companies from accounting firms, banks and credit unions, and aggregates the data at an approximate rate of 1, 000 statements a day.
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Sales trends for privately held companiesThrough its cooperative data model, Sageworks collects financial statements for private companies from accounting firms, banks and credit unions, and aggregates the data at an approximate rate of 1, 000 statements a day.
To get the data for the model, I would use FactSet data.
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But to maximize profitability under this data sales model, Facebook wants to drive the cost of data center infrastructure to some point below that of commodity boxes servers and storage arrays for example.
In contrast, a NoSQL database provides a more flexible data model, and it can be scaled across multiple machines.
That will ultimately have to be put into a computer and come up with the data model for the Gulf.
The standard data model Salesforce has is well suited to this strategy.
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The CRM data model is centered around people with lots of other abstractions that can be used for a variety of different purposes.
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He replied that the company preferred to make it easy to extend the data model in any way you wanted instead of trying to predict your needs.
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We can achieve a 6x performance speedup and we can drive that to 16x by using a simpler MapReduce model to avoid data motion more efficiently than Hadoop.
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Profitability of privately held gas stationsThrough its cooperative data model, Sageworks collects financial statements for private companies from accounting firms, banks and credit unions, and aggregates the data at an approximate rate of 1, 000 statements a day.
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Simply put, the model is the data (and by extension the HTML content of a website or app), the view is what you see on the screen (defined by the CSS styles of the user interface) and the controller is the logic that ties the two together (often expressed as the JavaScript or other interactive programming).
Figuring out a data-ubiquity model means first looking at the feasibility of creating data and consuming data deluges in your operations.
By virtue of the new model and remote sensing data fresh floodplain maps may be prepared, replacing the present one.
If yes, and you can think up a feasible data-ubiquity business model, you may have a top-level case for Big Data.
In Fall of 2009, we did just that and retrained a model using CDC ILI data from 2003 through summer of 2009 as the target.
Once a model is created, data scientists ideally will begin working with others to help test the models and set them in motion toward commercial application.
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Analytics is the second phase of the maturity model in which the data collected in the visibility phase is put to use in a variety of ways.
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So, we really would like to be able to check out the Clio NXT, the next-gen model being developed by Data Evolution, which bought the rights to the product from original maker Vadem.
The Forecast Model builds upon the output of the Stock Valuation Model and combines this data with econometric and simulation techniques to output target prices for one, three, and six-month and one, two, and three-year time horizons.
But when you apply the OBR's model to the economic data we've had since April, it looks very much as though they will have revised up that totemic measure of borrowing, yet again, for this Autumn Statement.
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