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OmniSci: Instant, Powerful, & Effortless

At OmniSci, our mission is to make analytics instant, powerful, and effortless for everyone. Interactively explore billions of data points and glean hidden insights - those single data points - that crack humanity's most pressing problems.
Recorded Oct 21 2019 2 mins
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Presentation preview: OmniSci: Instant, Powerful, & Effortless

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  • Accelerated Analytics Fit for Purpose: Scaling Up & Out Recorded: Mar 22 2020 31 mins
    Venkat Krishnmurthy, VP of Product, OmniSci
    OmniSci has demonstrated the massive scaling possible using GPUs for computation and visualization. However, not every analytics problem or user persona requires massive scale; rather, our customers have expressed the desire to have proper-sized tools for the various problems they encounter across the enterprise. This talk will outline the vision for scaling the OmniSci platform from trillions of records in a giant data store to hundreds of millions of records on a laptop and every form factor in between. Whether you have a massive cluster of servers, a Data Science Workstation, a GPU-enabled laptop or even a CPU-only laptop, OmniSci can provide the same accelerated analytics
  • OmniSci Opioid Demo Recorded: Mar 20 2020 6 mins
    New data shows more than 100 billion opioid pills were distributed nationwide from 2006-2014. Experience the power of accelerated analytics to unlock and visualize socially-impactful insights about a national public health crisis.
  • Using OmniSci for Interactive Exploratory Analysis with AWS Recorded: Mar 19 2020 24 mins
    Aaron Williams, VP of Global Community, OmniSci
    In this talk, we show how you can overcome the limitations of the existing analytics tools you use by using OmniSci on AWS Marketplace. OmniSci is an accelerated analytics platform that deploys quickly on AWS with NVIDIA GPU instances to query and visualize billions of rows of data delivering lower latency over other solutions. Using an open source analytics platform that deploys in Amazon’s cloud gives you the computational power and limitless capacity to scale the deployment. Learn about the range of different instances supported by OmniSci including P3 and G4 along with the variety of offerings we have with NVIDIA GPU support. Hear about use cases that help you correctly identify which offerings suit your needs the best and help you work on your data effortlessly with speed and scalability. Ram helps technology partners build, promote and sell their services to AWS customers and developers.
  • Instant Insight By Integrating Oil & Gas Data Assets Recorded: Jan 29 2020 58 mins
    Tyler Mitchell, Director of Product Marketing, OmniSci and Dan Gualtieri, Managing Director, Legato Energy Solutions
    Join Tyler and Dan as they discuss how the OmniSci platform is revolutionizing data analytics for large, integrated, disparate and complex datasets. Through the platform, oil and gas industry users are able to query, trend and visualize data in an innovative way across their corporate domain. Using powerful tools that understand geospatial and time-based data, OmniSci creates conversational based data analytic workflows.
  • OmniSci US Shipping Demo Recorded: Jan 24 2020 7 mins
    In this demo, over 11 billion rows of data of reflect ship movement throughout US coastal waters over a 7 year period. Watch as we dive into the waters of big data and see what kind of trends occurred during the Deepwater Horizon oil spill. By harnessing the power of the OmniSci platform, we're able to track activity down to a single ship!
  • Interactive Telco Market Sizing & Visualization Across Layers of Disparate Data Recorded: Oct 22 2019 30 mins
    Dustin Wright, Data Scientist, TELUS and Chris Havlin, Data Scientist, TELUS
    Learn how TELUS, a Canadian national telecommunications company, has created an interactive market sizing tool to grow subscribers and optimize network builds.

    TELUS’ high speed (HS) service can be provisioned over Fibre, Copper or over its mobile network. TELUS Marketing needs to have visibility over where each technology can be deployed, along with the targeting potential (number of households), and where its competitors offer similar services.

    Each technology type has its own coverage layers, qualification criteria and competitive restrictions, not to mention separate business units that design, implement and support the services they carry. Providing a “one stop shop” where Marketing can assess opportunity to build/grow subscribers as well as potential to improve network build prioritization, was highly desired.
    In rural areas where TELUS does not have the capability to offer HS over Fibre, HS over copper can be problematic in offering competitive speed plans, not to mention reliable service for customers. In these situations, TELUS offers HS over its LTE network to fixed line customers.

    With OmniSci, TELUS was able to build an interactive map for showing all of TELUS’ communities, along with, competitor speed information, wHSIA coverage layers, competitor cell sites, LTE coverage layers, household reference data, copper qualification, fibre eligibility, other exclusion layers, and marketable base (taking into account do not contact flags).
  • How Telecom Companies Break Through the Data Wall to Achieve Analytics at Scale Recorded: Oct 22 2019 52 mins
    Panel discussion with TELUS and Verizon, Moderator, Fraser Pajak
    Global mobile data traffic will exceed 49 exabytes per month by 2021. What new business opportunities does this data bring? How are telecom companies responding to the analytics challenges of data at this scale? We’ve brought together several telecom industry experts from Verizon and TELUS to discuss the future of telecom analytics.
  • Leveraging OmniSci to Support Geo-Semantic Pattern Detection in Large Data Sets Recorded: Oct 22 2019 53 mins
    Rich Sutton, VP Geospatial, Skyhook
    Skyhook Uses Omnisci for Insights in its High Volume, Globally Distributed Mobile Device Datapool

    Over the past decade and a half Skyhook has built and patented much of the technology used for accurately positioning mobile devices. This is accomplished by mixing Wi-Fi with cell and gps signals to deliver a best hybrid solution with extremely low latency regardless of local sampling challenges. Skyhook pioneered precision location for both iOS and Android and has deployed various solutions across billions of devices in these and other OS pools.

    In order to remain functionally accurate a global Wi-Fi database must self-heal through active field acquisition, and this requires massive MAU/DAU/HAU activity sustained indefinitely and retained as a structured artifact across multiple years.

    Skyhook’s various databases, including Wi-Fi access points, cell antennas, ip detections, signal confirmed venues and individual returned device locations produce high temporally and positionally accurate samples tens of billions of times daily. This raw output is refined and fractioned into specific data products that are useful to big data consumers in multiple industries and governments.

    OmniSci has proven itself highly performant in managing large volumes of point-based, time- and place-anchored data in a low latency analysis environment. We will show examples in areas where GPU-resident analytics permit Skyhook to scale and leverage vast data extracts into actionable insight in areas of crowd characterization, crisis-driven population dynamics, commercial consumer behavior and system pathology detection.
  • Practical Application of Deeply Geotemporal Data Recorded: Oct 21 2019 44 mins
    Dr Michael Flaxman, Founder at Geodesign Technologies
    Scientific applications often deal with deeply geotemporal data. These can include distributed sensor data streams, or high-repeat frequency satellite data. In this practical session, we review how to work with LIDAR, Sentinel-2 imagery, weather data and species telemetry data. Applications include climate change planning, continuous monitoring of fire and flood risk, and biodiversity analysis.
  • GPU-accelerated workflows & edge-compute with Lockheed Martin, NVIDIA & Z by HP Recorded: Oct 21 2019 27 mins
    Jared Dame, HP and James Waltner, Lockheed Martin and Brian Furtaw, NVIDIA
    Join us for an overview of how GPU-accelerated workflows are taken to a new-level with dual NVIDIA Quadro RTX 8000 GPUs on a Z by HP Data Science Solution. This session will walkthrough Z8 on-edge workflow experiences from Lockheed Martin and share how NVIDIA & Z by HP compliment data science platforms through increased power, usability and speed.
  • Flint Water Crisis: Data-Driven Solutions & Transparency Recorded: Oct 21 2019 33 mins
    Jared Webb, Chief Data Scientist, University of Michigan, BlueConduit
    In this session we’ll give you a brief overview of the Flint Water Crisis and how we made lead service line discovery more efficient during the City’s recovery. We’ll then present a comparative case study on the efficacy of data-driven models and using machine learning to replace service lines in Flint, versus a non data-driven approach. Finally, we’ll discuss our development and implementation of a public outreach tool: an interactive map for residents to observe replacement efforts, which includes up-to-date model predictions for every home in the city.
  • Impacting the Bottom Line with GPU-Powered Analytics on Customer Sourcing Data Recorded: Oct 21 2019 25 mins
    Will Webb, Analytics, Insight Sourcing Group
    What happens when the value of your data analytics department is challenged? How and when are you incorporating domain knowledge into your data? What sustainable approaches are you taking to measure ROI on data collection and presentation? Join Will Webb, part of Insight Sourcing Group’s advanced analytics leadership team, as he demonstrates how to use an analytics dashboard to answer these questions and help you drive bottom-line improvements.
  • Mapping the Invisible: Using Big Data, Geofiles, and GPU-power to Build More... Recorded: Oct 21 2019 31 mins
    Benjamin Pezzillo, Founder & CEO, Pactriglo
    Mapping the Invisible: Using Big Data, Geofiles, and GPU-power to Find Places to Build More Dwelling Units in Los Angeles.

    California faces a housing affordability crisis. Municipalities like Los Angeles regulate land use and zoning of private property. But even in this time of crisis, the City of Los Angeles lacks the capacity and/or desire to calculate and identify the unused density among the myriad of ordinances, restrictive overlays, and development incentives they administer. In this session, learn how Pactriglo is able to visualize tens of millions of data points from disparate sources to create a seamless real-time real estate data dashboard that guides real estate development projects to the path of least resistance.
  • OmniSci: Instant, Powerful, & Effortless Recorded: Oct 21 2019 2 mins
    At OmniSci, our mission is to make analytics instant, powerful, and effortless for everyone. Interactively explore billions of data points and glean hidden insights - those single data points - that crack humanity's most pressing problems.
  • Analyzing the Investment Market Using Alternative Data Recorded: Aug 14 2019 41 mins
    Venkat Krishnamurthy, VP of Product Management, OmniSci and Patrick Hogan, Senior Solutions Architect, NVIDIA
    Investment management firms seek alternative datasets, such as consumer transactions, logistics information, and employment trends, to improve trading strategies with an informational edge. This opens up new potential use cases that could allow investment management firms to analyze digital residue to value assets more accurately, on a near real-time basis, to visualize anomalies that may represent hidden portfolio risk, and to enhance investment analysis and capital market research. Yet the scale of these alternate data streams, often measured in billions of rows, has traditionally been too time-consuming or costly to examine.
  • OmniSci Demo: Telco Network Reliability Recorded: Aug 14 2019 4 mins
    Telecommunication network providers handle billions of transactions, usage logs, and data packets everyday- this is far too much data for mainstream analytics solutions to handle. With OmniSci, network providers are now able to accelerate SQL queries and visualize all telecommunications network data, without the data sampling required by their existing solutions. OmniSci gives network providers the power to visualize and analyze the entirety of their data in a seamless, interactive experience. This allows providers to spot customer impacting issues before the complaints start rolling in.

    OmniSci gives network providers the power to visualize and analyze the entirety of their data in a seamless, interactive experience. This allows providers to spot customer impacting issues before the complaints start rolling in.
  • Accelerate Your Operations in Telecom with AI Recorded: May 30 2019 61 mins
    Aaron Williams, OmniSci, Jared Ritter, Charter Spectrum, Eric Harper & Renee Yao, NVIDIA, Johanan Ottensooser, Datalogue
    In this webinar, you will learn:
    >why the telecom industry is evolving to make more AI-enabled data-driven decisions;
    >how GPU accelerated end-to-end data science solutions could speed time to insights; and
    >how specific machine learning techniques and models from NVIDIA GPU Cloud (NGC) can help your network orchestration, resource allocation in wireless networks and wireless communication links.
  • NVIDIA GTC 2019 Keynote | OmniSci Demo Recorded: Mar 23 2019 14 mins
    Jensen Huang, CEO of NVIDIA, and Aaron Williams, VP of Community at OmniSci
    Jensen Huang, CEO of NVIDIA, and Aaron Williams, VP of Community at OmniSci, present a predictive analytics demo on telecommunications network data from a major multi-service operator network provider.

    This provider must decide where to build the next wifi access points for over 25 million subscribers in order to help them offload traffic from 500,000 LTE towers. This will help them optimize traffic, save money, and improve customer experience.

    Aaron shows how AI can quickly ETL a terabyte of data. OmniSci is then used to visualize and analyze 500 million rows of data so quickly that it provides network analysts with a fully immersive, interactive analytics experience at the speed of curiosity.
  • GTC 2019: OmniSci & RAPIDS: End-to-End Open Source Data Science Workflow Recorded: Mar 20 2019 25 mins
    Venkat Krishnamurthy, VP of Product Management, OmniSci and Aaron Williams, VP of Global Community, OmniSci
    Learn how the OmniSci GPU-accelerated SQL engine fits into the overall RAPIDS partner ecosystem for open source GPU analytics. Using open data, OmniSci's Venkat Krishnamurthy,VP of Product Management and Aaron Williams, VP of Global Community, show how to ingest data that's from both streaming and standing sources, perform descriptive statistics and feature engineering using SQL and cuDF, and return the results as a GPU DataFrame. They also describe how data science workflow can be accomplished using tools from the RAPIDS ecosystem, all without the data ever leaving the GPU.
  • NVIDIA GTC 2019: How BMW Visualizes & Interacts with Extreme Datasets Recorded: Mar 13 2019 43 mins
    Caroline Persson, Data Scientist at the BMW Group, and Todd Mostak, CEO, OmniSci
    Connected vehicles generate a treasure trove of anonymized data with unlimited potential for the automobile industry. Vehicle usage, fleet movement, mobility patterns, telematics and spatiotemporal data are invaluable for everyone from development to manufacturing. Hear how the BMW Group has built dashboards with OmniSci Immerse to visualize this telematics data. View a demonstration of this application as it's used to visualize spatiotemporal telematics data and interact with massive datasets-in-motion with near-zero latency. Caroline Persson, Data Scientist at the BMW Group, and Todd Mostak, CEO of OmniSci, explain how the parallel processing power of GPUs unlocks a wealth of use cases across manufacturing and other major industries, driving operational analytics, geospatial analytics, and data science. Persson provides an example use case and shows how automobile manufacturers can ingest huge volumes of streaming telematics data coming from vehicles and apply machine learning models to descriptive driver behavior and patterns.
Massively Accelerated Analytics and Data Science
Interactively query, visualize, and power location intelligence workflows over billions of records.

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  • Title: OmniSci: Instant, Powerful, & Effortless
  • Live at: Oct 21 2019 3:40 pm
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