Remove Data Modelling Remove Data Visualization Remove User Experience
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Three Ways to Personalize Analytics to Improve User Experience

Sisense

In this article, we’ll explore three ways you can build a more personalized analytics experience for your customers and end users. The right data visualization will take your custom analytics to the next level. Explore data vis libraries. First, though, let’s get on the same page about what personalization is.

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Analyzing the history of Tableau innovation

Tableau

Visual encoding allowed people to quickly understand data through visual comparison rather than the mental math needed for grids of numbers. Even modern machine learning applications should use visual encoding to explain data to people. Another key data computation moment was Hyper in v10.5 (Jan Performance.

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An Expert Under the Hood: White-Label Reports and Dashboards

Sisense

The provider’s analytics platform plugs into your data source, crunches your numbers, and then generates reports and dashboard data visualizations. The right platform will give you total control over the widgets in your data visualizations, ideally in a user-friendly UI editor (like in Sisense’s Embedded Playground ).

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How does Tableau power Salesforce Genie Customer Data Cloud?

Tableau

Cut costs by consolidating data warehouse investments. Think of Tableau as your data visualization and business intelligence layer on top of Genie—allowing you to see, understand, and act on your live customer data. Open and extensible, Genie integrates seamlessly with your existing data architecture, including: .

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How does Tableau power Salesforce Genie Customer Data Cloud?

Tableau

Cut costs by consolidating data warehouse investments. Think of Tableau as your data visualization and business intelligence layer on top of Genie—allowing you to see, understand, and act on your live customer data. Open and extensible, Genie integrates seamlessly with your existing data architecture, including: .

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Must-Have AI Features for Your App

Sisense

In Augmented Apps , we examine how product teams are exploring AI and Machine Learning to make their products more intuitive and enhance the user experience. . Developing the right data model for your in-app AI is now a critical branch of programming, because correctly prepared data is vital to the algorithm model.

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The Rise of the Data Team

Sisense

These increasingly difficult questions require sophisticated data models, connected to an increasing number of data sources, in order to produce meaningful answers. Therein lies the power of your data team: Armed with know-how, they connect with the end user teams (internal users, product teams embedding insights, etc.)