nCodeDS Streamed Data Analytics

nCodeDS Streamed Data Analytics delivers performance and ease of use for analysing high volumes of digital bus data, connected vehicle data, and more.

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nCodeDS streamed data analytics transforms sensor data into actionable insights. Designed for scalable deployment within the web-based Aqira platform, nCodeDS (nCode Digital Streams) provides both the performance and the ease of use required to analyze high volumes of digital bus data, connected vehicle data and a wide range of other data sources.

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Discover how nCodeDS helps engineers gain meaningful insights through high performance data cleaning, transformation and engineering analytics.

Understand how products are used in the real world through sensor data analytics to help reduce development, operational and warranty costs.

nCodeDS directly reads a wide range of sensor data and measurement formats including time-stamped CSV files.

High volumes of data are efficiently streamed through nCodeDS processing networks at high velocity using multi-thread processing.

Avoid scripting from scratch by using built-in nCodeDS engineering capabilities such as cycle counting, time at level, damage calculations and FFT algorithms.

nCodeDS also integrates with Python modules to enable huge flexibility such as scientific math, statistical and machine learning capabilities.

Graphical drag and drop user interface makes creation of new processes easy for even the newest user.

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Actionable Insights from Stream Data Analytics

nCodeDS graphical interface enables simple, interactive definition of data processing networks required to analyze high volumes of sensor data coming from a wide range of sources.

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Analysis of Digital Bus and Network Data

Bus data is increasingly used for many applications beyond its initial purpose. These applications include usage monitoring, design validation, design enhancement, safety validation, etc.

Connected vehicles, for example, are making these sources of data readily available and offer the promise of transformational information. However, bus data raises a number of challenges, essentially due to the quality and quantity of data.

The next generation solution for these challenges is nCodeDS, a scalable analysis framework enabling engineers to gain actionable insights from streamed data analytics.

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Big Data Analytics in Engineering Applications

With the growing utilization of sensors, “big data” is a reality of life for engineering applications. In the pursuit of storing, searching and retrieving this data at scale, industries are looking at big data systems for data management solutions.

But the real question is: how do you extract value from big data? Many engineering applications require the application of sophisticated analyses and while generic big data tools are necessary for basic data management, they are inadequate for performing real-world engineering analysis.

This whitepaper introduces nCodeDS, a new software solution, designed specifically for efficiently analyzing large volumes of engineering time series data. Through examples, it will illustrate how to achieve greater value from insights gained through superior analytics in an engineering context.

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