Geospatial Analytics with Big Data: Five Steps for Creating Business Value

Organizations can gain powerful, actionable insights by combining maps, geographical data, and relevant “big data” sources such as customer behavior or sensor data. Leading firms in a variety of industries—including retail, real estate, energy, telecommunications, land management, and law enforcement—are today engaged in projects involving geospatial analytics, and broader interest is growing. TDWI Research, in a recent survey on emerging technologies, found that the number of respondents who stated that they would be using geospatial analytics will double over the next three years.
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Modernizing Data Architecture With Streaming CDC

Modernising Data Architecture with Streaming CDC Expanding analytics requirements have increased the appetite for massive data volumes. However, these data flows can create bottlenecks, preventing timely and modern analytics innovations such as machine learning. This is where streaming Change Data Capture (CDC) comes in.
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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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Redis Ingenuity Webinar Beyond Caching: AI-Powered Search with Redis

Search capability is ingrained into our daily life. How many arguments these days are settled with the conclusion, “Just Google it”??! We all expect some type of search functionality in every application and website. Meanwhile, advances in computer vision, natural language processing, large language models, and generative AI have made it possible to extract semantic properties from unstructured data in the form of vector embeddings. It can be daunting to query this kind of data, which combines K-Nearest Neighbors algorithms and lexical search, unless you have the right tool for the job. When you fail, performance suffers. Web users typically expect search results under one second.
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Architecting a Secure, Highly-Available Kubernetes Data Services Platform for Red Hat OpenShift

Attend this webinar to find out how Portworx and Red Hat are working together to help you run your Kubernetes applications. In this talk, learn how Portworx Kubernetes Data Platform delivers the enterprise-grade features you need to manage and automate the data in your Red Hat OpenShift on AWS (ROSA) environment while reducing the AWS infrastructure bill by up to 60%.
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