Name: User-Defined Algorithms on Big Data with OmniSci
Start: 2020-10-09T17:05:00Z
End: 2020-10-09T17:05:25.000Z
Location: BrightTALK
Rating: 0

HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data.

Experts from HEAVY.AI, NVIDIA and Bain Consulting share a comprehensive view of the industry's first radio frequency (RF) digital twin solution. HeavyRF enables telcos to simulate potential city-scale deployments as a faster, more efficient way of optimizing planning, coverage, and customer experience.

Telco Digital Twins: Connecting Customer Experience to Network Planning

This video will show you how to import Raster files into HEAVY.AI v6.0. 

Full 6.0 Release Page: https://www.heavy.ai/product/release/6-0  

HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data. HEAVY.AI supports high-impact decisions in previously unimaginable timelines by harnessing the massive parallelism of modern GPU and CPU hardware. This analytics capability unifies today’s exploding data volumes from multiple sources for a better immersive and real-time, interactive visual experience.

How To Import Raster Files | HEAVY.AI v6.0

This video will show you how to use HeavyConnect in HEAVY.AI 6.0

Full 6.0 Release Page: https://www.heavy.ai/product/release/6-0  

HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data. HEAVY.AI supports high-impact decisions in previously unimaginable timelines by harnessing the massive parallelism of modern GPU and CPU hardware. This analytics capability unifies today’s exploding data volumes from multiple sources for a better immersive and real-time, interactive visual experience.

How To Use HeavyConnect | HEAVY.AI v6.0

This video will show you how to access the Admin Portal in HEAVY.AI 6.0. 

Full 6.0 Release Page: https://www.heavy.ai/product/release/6-0  HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data. HEAVY.AI supports high-impact decisions in previously unimaginable timelines by harnessing the massive parallelism of modern GPU and CPU hardware. This analytics capability unifies today’s exploding data volumes from multiple sources for a better immersive and real-time, interactive visual experience.

How To Access The Admin Panel | HEAVY.AI v6.0

In this webinar, we will demonstrate 3 common utility analytics workflows, and how GPU analytics can be used to accelerate them: strike tree analysis, PSPS event planning and demand management.

Powering Next-Gen Utility Analytics

This video will show you how to use gauge charts in the HEAVY.AI v6.0 release. 

Full 6.0 Release Page: https://www.heavy.ai/product/release/6-0

HEAVY.AI provides advanced analytics that empower businesses and the government to visualize high-value opportunities and risks hidden in their big location and time data. HEAVY.AI supports high-impact decisions in previously unimaginable timelines by harnessing the massive parallelism of modern GPU and CPU hardware. This analytics capability unifies today’s exploding data volumes from multiple sources for a better immersive and real-time, interactive visual experience.

How To Use Gauge Charts | HEAVY.AI v6.0

The HEAVY.AI support team will walk you through how to use text charts in the HEAVY.AI platform. 

HEAVY.AI Introduces New Capabilities that Enable Organizations to Gain Faster Access to Rapidly Growing Data Sets and Deliver Decision-Quality Information.

How To Use Text Charts | HEAVY.AI

HEAVY.AI 6.0 introduces HeavyConnect, a zero-copy approach to fast data connectivity, and offers no-code visualizations of machine learning inference, empowering stakeholders to make timely, informed decisions

Full Release Page: https://www.heavy.ai/product/release/6-0
Get Started with HEAVY.AI Free: https://www.heavy.ai/product/downloads

What's New in Version 6.0?

Using California as a case, we'll consider forest structure data from the California Forest Observatory, also generated using machine learning models. At 10 meters per pixel, this amounts to 400 million pixels per time slice (4) per variable (5). To concentrate on wildfire risk for households, we use the fire science concept of “defensible space” and buffer buildings to extract surrounding forest conditions. Then we apply supervised techniques such as Random Forests so that we can explore the factors correlated with particular outcomes.

To learn more about HEAVY.AI, visit http://www.heavy.ai.

Improving Utilities' Vegetation & Fire Incident Management w/ GPU Analytics

Serious wildfires, floods, and natural disasters will continue to threaten lives and property until we change how we manage our forests, wildland/urban interfaces, and utility networks. But exactly where, when, and how must we act? We demonstrate how HEAVY.AI uses GPU analytics to help major utilities improve their vegetation management, weather prediction, and fire incident management capabilities to mitigate the risks of natural disasters. We take a holistic approach, building systems that natively handle a variety of big geotemporal data types, including lidar, multispectral drone and satellite data, and multiple weather models.

To learn more about HEAVY.AI, visit http://www.heavy.ai.

Mitigating Risk of Natural Disaster with GPU accelerated Analytics

This talk shows how business and government users can create interactive geotemporal dashboards able to render and cross-filter billions of geographic features with no code on HEAVY.AI 6.0. We also highlight our extensibility, including rapid generation of light-code web apps using pretrained machine learning models for object detection and semantic segmentation. Lastly, we show how Python coders, such as data scientists, can further extend the platform to add new SQL functions running in parallel on GPU with a single line decorator.

To learn more about HEAVY.AI, visit http://www.heavy.ai.

What is the Future of GPU-Accelerated Analytics?

Learn how modern data science techniques and GPU-advanced analytics can be combined with census demographic and California Forest Observatory data to improve wildfire outcomes.

Mitigating the Risk of Wildfires with Advanced Analytics

In this webinar, we share the latest release highlights, deliver demonstrations of core features, and provide examples of how you can apply HEAVY.AI's newest capabilities to your critical workflows.

A New Era of Advanced Analytics for Decision-Making

This webinar will show you how we developed a dot density dashboard to visualize over a billion points counts across the United States and the previous four Censuses. We'll explore population movement by ethnicity, areas of redistricting conflict, and examples of historical redlining while highlighting the spatial data science practices that made the visualizations possible.

To learn more about OmniSci, visit http://www.omnisci.com.

Mapping 30 Years of Census Data with Dot Density in OmniSci

With the release of Shang Chi and the Legend of the 10 Rings right around the corner, it's the perfect time to do a comparative analysis on the overall power levels of the characters in the film using OmniSci's Comic Superheroes Dashboard.   

This dashboard allows users to gain insight into superheroes and supervillains from almost every comic book franchise. Watch us analyze their backgrounds, appearances, power levels, and superpowers quicker than a Thanos snap!

All sequences and clips used in this video fall under Fair Use:
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Fair use is a user permitted by copyright statute that might otherwise be infringing. Non-profit, educational, or personal use tips the balance in favor of fair use.

All rights and credit go directly to its rightful owners. No copyright infringement intended.

Comic Book Heroes and Villains: A Comparative Analysis

This stream is a Let's Explore of our 100+ Years of NOAA Weather Data blog, featuring special guest, Kyle Pennell. You can check out the blog here: https://www.omnisci.com/blog/100-years-100-million-records

Let's Explore - 100+ Years of NOAA Weather Data

In response to the growing threat of wildfires, the current administration assembled Governors from Western states, Cabinet officials, and various partners on June 30th, 2021.

They discussed ways to protect communities across the country from wildfires and their devastating impacts by strengthening fire prevention, preparedness, mitigation, and response efforts, including a need to enhance our utilization of data and technology to protect communities.

This webinar will explore how OmniSci can play a critical role in understanding factors contributing to wildfires, associated risks, and impacts on communities across the Western United States, Canada, and beyond.

Specifically, we'll examine the probability of four and eight-foot flames across California and the cross-section of electrical transmission lines, street networks, building footprints, and data representing vulnerable populations living and working in those spaces.

Preventing the Next Paradise Disaster with Accelerated Analytics

Utilities have long spent considerable time, attention, and treasure on vegetation management, often yielding disappointing or catastrophic results.

California utilities, for example, have been responsible for several deadly and costly fire events, despite spending more than 1B dollars per year on utility vegetation management.

While this issue has received widespread public and utility industry consideration, very few approaches are available that are scientifically accurate, up-to-date, and scalable.

This webinar shows how OmniSci enables organizations to orient big geospatial data toward advanced vegetation management and efficient risk mitigation.

Specifically, we'll explore the cross-section of tree health & mortality, electrical transmission lines, weather, and the probability of four and eight-foot flames across California.

Interpreting Datasets for Wildfire Risks in the American West

OmniSci is designed for big data but for custom computations the data needs to be retrieved to a client machine. This puts a ceiling on data sizes based on both network speed and local hardware resources. What if we could send the algorithm to the data instead?

User-Defined Algorithms on Big Data with OmniSci

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Big Data Management

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User-Defined Algorithms on Big Data with OmniSci

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