Sentence examples for big data storing and from inspiring English sources

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A later study [99] presented a general architecture of big data analytics which contains multi-source big data collecting, distributed big data storing, and intra/inter big data processing.

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It has also pledged to create a big data store, collecting and analysing information from previously unconnected databases to influence services across the UK's growing cities.

A machine learning model: Once you have a big data store, data sources and data linkage established, you need to set up artificial intelligence (AI) and machine learning models that can automatically analyze data feeds, establish baselines and risk score activity without being programmed.

In this era of cloud-based connectivity and big data stores, logistics companies can, more than ever, model supply chain synergies for their customers.

In this day and age of plummeting storage costs and ubiquitous (free!) big data stores, if you're not capturing every single bit of data, you're doing something wrong.

A further generation of "enabling technologies" - artificial intelligence, "big data" stores, crowd-sourcing, virtual meeting rooms and affective computing, which aims to detect human emotions - could lead to more sophisticated online justice in future, the report contemplates.

These interactions are, via the knowledgde database, derived form wet lab experiments in the literature, and from big data stored in curated public databases (GEO, etc).

Before embarking on any large scale AI effort, a brand should ensure that the data from all the operational systems are pipelined and warehoused in a big data store for consumption by the AI solutions.

We're not quite that extreme now, as our tool sets have gotten more powerful and accessible over time, but we still provide classes on SQL and other tools, and expect our people can query our big data stores for what they need to manage their operations.

That summer, a core group of its creators, committers and contributors formed Sqrrl to allow organizations and businesses to have secure, scalable and easily adaptable ways to manage their own big data stores.

And the sheer amount of data in the average big data store introduces another potential security risk - the cloud.

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