Remove products experience-data-and-insights
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Unlocking the power of data sharing: 4 highlights from Data Citizens ‘24

Collibra

At Data Citizens ‘24, industry leaders and experts converged to explore how they could do more with trusted data. For many attendees, this meant exploring the transformative potential of data sharing. Data Citizens offered multiple opportunities to gain practical insights and real-world examples this year.

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IBM and TechD partner to securely share data and power insights with gen AI

IBM Big Data Hub

As technology expands, at TechD , we know that the quality of generative AI (gen AI) depends on accurate data sourcing. A reliable and trustworthy data source is essential for sharing information across departments. This addresses data management, conversational interface and natural language processing needs with efficiency.

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Drive customer success with OpenText Experience Cloud 24.2

OpenText Information Management

Traditional metrics like acquisition, onboarding and loyalty might look okay at first glance, but could be masking underlying issues like high turnover, frustration, and fractured experiences. OpenText™ Experience Cloud Edition 24.2 continues to innovate with a holistic approach to customer experiences and customer success.

Cloud 57
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Elevate human potential with Cloud Editions (CE) 24.2

OpenText Information Management

Titanium X represents our strategic product roadmap to provide a common platform for consuming all OpenText software and services, delivered by CE 25.2. We continue to integrate cutting-edge AI directly into our products, creating solutions that are not only responsive but anticipator as we revolutionize the very essence of work.

Cloud 96
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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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Elevate human potential with Cloud Editions (CE) 24.2

OpenText Information Management

Titanium X represents our strategic product roadmap to provide a common platform for consuming all OpenText software and services, delivered by CE 25.2. We continue to integrate cutting-edge AI directly into our products, creating solutions that are not only responsive but anticipator as we revolutionize the very essence of work.

Cloud 94
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AI transforms the IT support experience

IBM Big Data Hub

Product-embedded or online support tools, such as virtual assistants, can drive more informed and efficient support interactions with client self-service. As a developer of AI, IBM works with thousands of clients to help them infuse the technology throughout their enterprise for new levels of insights and efficiency.

IT 74
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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. This framework explains how application enhancements can extend your product offerings. How much value could you add? Brought to you by Logi Analytics.

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5 Early Indicators Your Embedded Analytics Will Fail

Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late. In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.".

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How to Build Data Experiences for End Users

Organizational data literacy is regularly addressed, but it’s uncommon for product managers to consider users’ data literacy levels when building products. Product managers need to research and recognize their end users' data literacy when building an application with analytic features.