Remove Big Data Remove IoT Remove Risk Remove Structured Data
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Using Artificial Intelligence to Make Sense of IoT Data

BizAcuity

IoT is basically an exchange of data or information in a connected or interconnected environment. As IoT devices generate large volumes of data, AI is functionally necessary to make sense of this data. Data is only useful when it is actionable for which it needs to be supplemented with context and creativity.

IoT 56
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New Software Development Initiatives Lead To Second Stage Of Big Data

Smart Data Collective

The big data market is expected to be worth $189 billion by the end of this year. A number of factors are driving growth in big data. Demand for big data is part of the reason for the growth, but the fact that big data technology is evolving is another. Structured. Semi-structured.

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Generative AI is pushing unstructured data to center stage

CIO Business Intelligence

Unlike that energy company, many organizations have yet to feel an urgency to capitalize on the value of their vast reservoirs of unstructured data. After all, we in the information management and technology industry have talked at length about unstructured data since “Big Data” was big news more than a decade ago.

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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge. What is Big Data Fabric?

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 166
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Different Types of Databases for Modern Data Challenges

Sisense

We live in an era of Big Data. The sheer volume of data currently existing is huge enough without also grappling with the amount of new information that’s generated every day. It’s no wonder, then, that NoSQL databases are seeing a lot of use in Big Data and real-time web apps. Cloud Solutions. Decision Time.