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Optimize queries using dataset parameters in Amazon QuickSight

AWS Big Data

Then the visuals in the dashboard react to the user’s selection of parameter value. With dataset parameters, authors can optimize the experience and load time of dashboards that are connected live to external SQL-based sources. Choose the table visual and add a few columns from the Fields list.

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Super-charged pivot tables in Amazon QuickSight

AWS Big Data

Additionally, with Amazon QuickSight Q , end-users can simply ask questions in natural language to get machine learning (ML)-powered visual responses to their questions. This involved migrating complex tables and pivot tables, helping them slice and dice large datasets and deliver pixel-perfect views of their data to their stakeholders.

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Sisense Q4 2020: Analytics for Every User With AI-Powered Insights

Sisense

Often, to find those types of insights, you slice, dice, and filter. As another example, if your sales went up by 10%, Sisense might explain that the increase was attributable to both a specific product category and a certain age group of customer with a visual display of the breakdown.

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Trakstar unlocks new analytical opportunities for its HR customers with Amazon QuickSight

AWS Big Data

It’s powered by Amazon QuickSight , a cloud-native business intelligence (BI) tool that enables embedded customized, interactive visuals and dashboards within the product experience. The power of QuickSight lets our customers slice and dice the data in different ways. question when it comes to talent acquisition and other areas.

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Sisense’s Q2 Release: A Modern Data Experience Across the Analytics Continuum

Sisense

In-Warehouse Data Prep provides builders with the advanced functionality they need to rapidly transform and optimize raw data creating materialized views on cloud data warehouses. Additional capabilities.

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It's Not The Ink, It's The Think: 6 Effective Data Visualization Strategies

Occam's Razor

Too many bars, inside them too many slices, odd color choices, all end up with this question: what the heck's going on here? It also forces a lot less think than might be optimal. What you want to do instead is to do all the slicing, dicing, segmentation, beautiful math, and then step above it. Interesting trend.

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Experimenting to Win with Data

Sisense

The experiences of Measuremen, an international consultancy that helps organizations optimize facilities use, illustrate this point. Since 2005, Measuremen has helped its clients study and optimize facilities use. Measuremen can visualize the data in its portal, evaluate current trends, and recommend changes.