Data Storytelling With Multiexperiences

Discussion Topics:
- What is a data story
- When and how should data storytelling be used
- Which new skills and techniques do you need to create compelling data stories
- Which experiences can help tell your story beyond dashboards on a 2D screen
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Spotlight

OTHER ON-DEMAND WEBINARS

Data and Analytics Trends for 2019 and Beyond: A Panel Discussion

Gartner

Discussion Topics: - How effective are your current data and analytics initiatives - What trends will most impact how you utilize data and analytics in 2019 and beyond - What must you do to maximize data and analytics in your organization
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Data Architecture Best Practices for Advanced Analytics

Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need. There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
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Top 7 Capabilities for Next-Gen Master Data Management

Reltio

This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.
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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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