Rocket-Powered Data Science

SEPTEMBER 25, 2022

It is an insight engine, providing not only data for descriptive and diagnostic analytics applications, but also providing essential data for predictive and prescriptive analytics applications. The digital twin is more than a data collector. 4) The DT Canvas (chapter 4)!

Diagnostic Analytics 214

Diagnostic Analytics Prescriptive Analytics Internet of Things IoT 214

Rocket-Powered Data Science

MARCH 19, 2021

One of the primary drivers for the phenomenal growth in dynamic real-time data analytics today and in the coming decade is the Internet of Things (IoT) and its sibling the Industrial IoT (IIoT). One group has declared , “IoT companies will dominate the 2020s: Prepare your resume!” trillion by 2030. trillion by 2030.”.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

Rocket-Powered Data Science

JULY 19, 2023

Accompanying the massive growth in sensor data (from ubiquitous IoT devices, including location-based and time-based streaming data), there have emerged some special analytics products that are growing in significance, especially in the context of innovation and insights discovery from on-prem enterprise data sources.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

AWS Big Data

FEBRUARY 20, 2024

You can ingest and integrate data from multiple Internet of Things (IoT) sensors to get insights. However, you may have to integrate data from multiple IoT sensor devices to derive analytics like equipment health information from all the sensors based on common data elements.

IoT 94

IoT Analytics Prescriptive Analytics Internet of Things 94

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Prescriptive Analytics

Rocket-Powered Data Science

JULY 14, 2023

When data science was in its “early days” within businesses, the data scientists mostly worked offline with static sources (like databases or web-based reports) to build and test analytics models for potential deployment in the enterprise.

Analytics 165

Analytics Internet of Things Prescriptive Analytics Data Science 165

Cloudera

FEBRUARY 4, 2019

It is a key capability that will address the needs of our combined customer base in areas of real-time streaming architectures and Internet-of-Things (IoT). It meets the challenges faced with data-in-motion, such as real-time stream processing, data provenance, and data ingestion from IoT devices and other streaming sources.

IoT 72

IoT Prescriptive Analytics Digital Transformation Internet of Things 72