Leveraging Big Data to Improve Traffic Incident Management NCHRP 2017 75

As the era of “Big Data” is upon us, there is an overwhelming number of data sources to draw from to improve traffic incident management (TIM). Big Data is not just “a lot of data,” it is a fundamental change in how to collect, analyze, and use data to uncover trends and relationships. In general, advances in technology have significantly increased data quantity, improved data quality, and enhanced data analytics. There is an urgent need for transportation agencies to become fluent in these technologies and to successfully integrate them within their operations so that they may benefit from the large set of existing and emerging Big Data data sources and tools. Big Data holds the potential for leveraging the greatest return on investment in traffic incident management and associated public safety outcomes.
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OTHER ON-DEMAND WEBINARS

Setting Up a Data Integration Pipeline for Repeatable Analytics Delivery

GoodData Corporation

As part of its platform, GoodData provides a fault-tolerant, high performance and scalable system for data integration. While built for large-scale analytic applications, it is a metadata-driven, modular system that can start small and grow with your business. In this session, Cameron demonstrates how to set up and schedule regular data extraction from SQL databases and other sources. He also covers some of the issues requiring attention in data extraction such as data merging and incremental loads. A future session will cover transformations and data enrichment along with data distribution.
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Delivering Real-Time Business Insights from ERP Data in the Cloud

Businesses succeed when they can extract more contextual, relevant, and predictive insights from ERP data in real time. ERP analytics can deliver more powerful data-driven insights if deployed in a cloud-based platform. The scalability of cloud-based data repositories—such as data lakes and data warehouses—can allow more users to concurrently query, explore, correlate, analyze, and visualize more ERP data more rapidly than would be possible on many on-premises analytics platforms.
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Enabling the Third Wave of Analytics: Embedded BI Takes Center Stage

GoodData

Today’s data-savvy companies actively seek ways to enhance their approach to analytics and evolve out of the past. While the first wave of BI involved static, rigid, IT-owned systems, and the second expanded the capabilities to a more business-facing analyst set, the third wave aims to infuse analytical activity into multiple layers of non-technical business roles. As a key strategy to enable this third wave, companies today are exploring an embedded approach that places analytical activity directly in the context of everyday user applications, and the independent software vendors (ISVs) and enterprises providing those applications have taken notice of this trend. Done efficiently, embedded analytics promotes faster deployment and pervasive usage of analytics for end-users while delivering a competitive advantage and the opportunity for new revenue streams for software vendors and enterprises.
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How Atrium Health Augments Utilization Review with Artificial Intelligence

XSOLIS

Tonya Harrison, Director of Clinical Care Management at Atrium Health (formerly Carolinas HealthCare System), discusses how Atrium Health is using artificial intelligence technology and predictive analytics to help review cases, resulting in significant time savings and increased compliance.
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