Remove IoT Remove Risk Remove Statistics Remove Structured Data
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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

Analytics 166
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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

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Business Intelligence Dashboard (BI Dashboard): Best Practices and Examples

FineReport

Data Visualizations : Dashboards are configured with a variety of data visualizations such as line and bar charts, bubble charts, heat maps, and scatter plots to show different performance metrics and statistics. Financial dashboards are useful for monitoring business performance and for financial planning and analysis.

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Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

There are essentially four types encountered: image/video, audio, text, and structured data. That’s most likely a mix of devops, telematics, IoT, process control, and so on, although it has positive connotations for the adoption of reinforcement learning as well. Spark, Kafka, TensorFlow, Snowflake, etc.,

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What is a Data Pipeline?

Jet Global

Real-Time Analytics Pipelines : These pipelines process and analyze data in real-time or near-real-time to support decision-making in applications such as fraud detection, monitoring IoT devices, and providing personalized recommendations. As data flows into the pipeline, it is processed in real-time or near-real-time.