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Description
Real-time monitoring of rainfall through rain gauges enables operations personnel to be alerted about potential flooding or sewer overflow situations. By closely tracking and evaluating precipitation levels at various sites, it becomes possible to estimate rainfall in areas that are not directly monitored, a method known as the “Distributed Rainfall Modelling Technique” (DRMT). The integration of rainfall radar data with readings from rain gauges facilitates the creation of enhanced rainfall coverage maps. Furthermore, examining historical rainfall data helps in constructing rainfall intensity-duration curves, which can be compared to the design intensity-duration-frequency curves of the region, aiding in the identification of return periods for recorded events through forensic analysis. In addition, new intensity-duration-frequency curves can be generated to inform the design of drainage infrastructure, including sewers, channels, and storage facilities. Continuous flow monitoring, coupled with data analysis, contributes to the development of rainfall versus stormwater runoff response curves, which are essential for calibrating drainage system models effectively. This comprehensive approach ensures that urban planning and flood management strategies are well-informed and responsive to actual conditions.
Description
Conventional techniques for integrating mainframe data, such as ETL, data warehouses, and connector development, are increasingly inadequate in terms of speed, accuracy, and efficiency in today’s business landscape. As the amount of data generated and stored on mainframes continues to surge, these outdated methods fall further behind. Data virtualization emerges as the solution to bridge this growing divide, automating the accessibility of mainframe data for developers and applications alike. This approach allows organizations to discover and map their data just once, after which it can be easily virtualized and reused across various platforms. Ultimately, this capability enables your data to align with your business goals and aspirations. By leveraging data virtualization on z/OS, organizations can simplify the complexities associated with mainframe resources. Moreover, data virtualization facilitates the integration of data from numerous disparate sources into a cohesive logical repository, significantly enhancing the ability to connect mainframe information with distributed applications. This method also allows for the enrichment of mainframe data by incorporating insights from location, social media, and other external datasets, promoting a more comprehensive understanding of business dynamics.
API Access
Has API
API Access
Has API
Integrations
IBM Cloud
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Smart City Water
Country
Canada
Website
smartcitywater.ca/datacurrent/
Vendor Details
Company Name
Rocket
Founded
1990
Country
United States
Website
www.rocketsoftware.com/product-categories/data-virtualization