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| # vehicle-telematics-analytics-demo | ||
| Real-time vehicle telematics analytics demo using OmniSci | ||
| Real-time vehicle telematics analytics demo using OmniSci, debuted at [NVIDIA GTC 2019](https://www.nvidia.com/en-us/gtc/) San Jose. | ||
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| ## Real-Time Dash App | ||
| This demo is built using only open-source components: | ||
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| - [OmniSci Core](https://github.com/omnisci/mapd-core) | ||
| - [pymapd](https://github.com/omnisci/pymapd) | ||
| - [StreamSets Open Source](https://streamsets.com/opensource) | ||
| - [Apache Kafka](https://kafka.apache.org/) | ||
| - [Dash by Plotly](https://plot.ly/products/dash/) | ||
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| This repo is set up as a monorepo; see the [data engineering](https://github.com/omnisci/vehicle-telematics-analytics-demo/tree/master/dataengineering) and [f1dash](https://github.com/omnisci/vehicle-telematics-analytics-demo/tree/master/f1dash) folders for the README's for StreamSets and Python/Dash code, respectively. | ||
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| ## Data | ||
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| We want to see what YOU would build with this dataset! | ||
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| In addition to providing all of the code, OmniSci is providing the data for all laps in an S3 bucket. The table definitions are in the [ddl folder](https://github.com/omnisci/vehicle-telematics-analytics-demo/tree/updatereadme/ddl); use OmniSci Core or OmniSci Cloud to load the data and to perform your queries, then use OmniSci Immerse or your favorite visualization tool to explore the data. | ||
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| Please be respectful and make a copy to your own location rather than direct-linking against this bucket: s3://mapd-cloud/DataSets/vehicle_telematics_dataset_f12018/ |