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OmniSci
概述
公司介绍
OmniSci 是加速分析的先驱。 OmniSci 平台用于商业和政府部门，以发现超出主流分析工具限制的数据洞察力。利用现代 CPU 和 GPU 硬件的大规模并行性，该平台可在云端和内部部署中使用。 OmniSci 起源于哈佛大学和麻省理工学院计算机科学与人工智能实验室 (CSAIL) 的研究。 OmniSci 由 GV、In-Q-Tel、New Enterprise Associates (NEA)、NVIDIA、Tiger Global Management、Vanedge Capital 和 Verizon Ventures 资助。该公司总部位于旧金山。在 www.omnisci.com 上了解有关 OmniSci 的更多信息。
物联网解决方案
Accelerated Analytics Platform Accelerated Analytics Platform OmniSci 平台旨在克服面对当今大数据集的规模、速度和位置属性的传统分析工具的可扩展性和性能限制。这些工具正在崩溃，变得太慢且太耗费硬件，无法有效地进行大数据分析。 OmniSciDB 开源 SQL 引擎 该平台的基础是 OmniSciDB，它是世界上最快的开源分析数据库。 OmniSciDB 利用 GPU 和 CPU 的强大功能并在几毫秒内返回 SQL 查询结果，即使在具有数十亿行的表上也是如此。 OmniSciDB 结合了对本机 SQL、快速查询编译、查询向量化和高级三层内存管理的支持，提供了极致的大数据分析性能。 OmniSci Render 服务器端视觉渲染 OmniSci Render 是一个服务器端引擎，设计用于渲染海量数据集的点图、散点图和多边形可视化。这为用户提供了零延迟、与复杂可视化的探索性交互，这在以前是不可能的。对于地理空间可视化，Vega 渲染引擎 API 允许用户可视化多达数十亿个点、线或多边形。 OmniSci Immerse 交互式可视化分析 OmniSci Immerse 是一个基于 Web 的数据可视化界面，利用 OmniSciDB 和 OmniSci Render 的加速速度和渲染功能实现无与伦比的可视化交互。 OmniSci Immerse 非常直观且易于使用，提供标准的可视化，例如折线图、条形图和饼图，以及复杂的数据可视化，例如地理点图、地理热图、等值线和散点图。仪表板在与数据交互时自动交叉过滤，并以零延迟刷新。数据集成 将数据源连接到 OmniSci OmniSci 开源了 OmniSciDB SQL 引擎，使用户和开发人员可以轻松轻松地加速分析和数据科学工作负载。 OmniSciDB 可在 GitHub 上获得 Apache 2.0 许可，以及 Python 接口 (pymapd) 和 JavaScript 基础架构（omnisci-connector、omnisci-charting）等其他组件，使 OmniSci 成为开源加速分析领域的领导者。
物联网应用简介
技术栈
OmniSci的技术栈描绘了OmniSci在平台即服务 (paas), 应用基础设施与中间件, 分析与建模, 和 网络与连接等物联网技术方面的实践。
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应用层
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配套技术
技术能力:
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中等
强
实例探究.
Case Study
Leveraging IoT for Enhanced Network Analytics: A Case Study on TELUS and HEAVY.AI
TELUS, a leading telecommunications company, was faced with the challenge of interactively exploring complex network datasets without experiencing lag. The company needed a comprehensive mapping of TELUS communities and competitor speed information to better understand the market dynamics. Identifying competitor coverage and deciding where to build wireless services was another significant challenge. Each of TELUS’s high-speed services has its own coverage layers, qualification criteria, and competitive restrictions. TELUS Marketing needed to know where they could deploy each service, the targeting potential, and where competitors offer similar services. They required an advanced analytics solution that quickly shows their customer base, potential upsell opportunities, and where wireline and wireless high-speed internet adoption are low.
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