Articles

The Role of Relays In Big Data Integration

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The very nature of big data integration requires an organization to become more flexible in some ways; particularly when gathering input and metrics from such varied sources as mobile apps, browser heuristics, A / V input, software logs, and more. The number of different methodologies, protocols, and formats that your organization needs to ingest while complying with both internal and government-mandated standards can be staggering.

Is there a clean and discreet way to achieve fast data integration and still reap all of the benefits of big data analytics?

Source de l’article sur DZONE

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4 Examples of Connecting Data To ML and AI

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Data that has been collected, collated, and cleansed is ripe for analysis and insight generation. Advances in Machine Learning and AI are helping deliver on the promises of augmented analytics to produce actionable insights. Pairing Machine Learning techniques with prepared data enables organizations to achieve more accurate predictions and measurable analysis on all kinds of business functions.

A growing number of BI and Analytics tools vendors are responding to the need for augmented BI by opening their platforms through APIs and making stored data more easily accessible. This is a critical first step that gives IT the ability to build connections from Machine Learning products to raw, cleaned, and prepared data.


Source de l’article sur DZONE (AI)

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