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Optimize queries using dataset parameters in Amazon QuickSight

AWS Big Data

With dataset parameters, authors can optimize the experience and load time of dashboards that are connected live to external SQL-based sources. Optimized custom SQL in direct queries With dataset parameters, you no longer have to trade-off between the flexibility of using custom SQL logic and the performance of an optimized SQL query.

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How OLAP and AI can enable better business

IBM Big Data Hub

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Cost optimization : Optimizing cloud spending for OLAP resources can be challenging due to complex pricing models and resource utilization patterns.

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

AWS Big Data

Because QuickSight is fully managed and serverless, we were able to focus on building value for customers and develop an embedded dashboard delivery solution to support all three products, rather than focusing on managing and optimizing infrastructure. The power of QuickSight lets our customers slice and dice the data in different ways.

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Super-charged pivot tables in Amazon QuickSight

AWS Big Data

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. For example, a customer 360 report sliced by different regions. Recently, Amazon FinTech migrated all their financial reporting to QuickSight.

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In Times of Rapid Change, Business Process Modeling Becomes a Critical Tool

erwin

The key point is that useful change comes from routinely looking at process models and spotting a sub-optimality. There’s a clear connection between business process modeling and digital transformation initiatives. Bringing IT and Business Together to Make More Informed Decisions. BPM for Regulatory Compliance. Change Is Constant.

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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. Code-savvy users can crack open the optimized SQL code that drives live visualizations to easily understand and validate the logic. Every company is becoming a data company; there’s no getting around it. Smarter insights with AI-powered data explanations.

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How Model Observability Provides a 360° View of Models in Production

DataRobot Blog

This poses a critical challenge as these models continuously influence key business decisions, such as loans provisioning in financial services , inventory forecasting in retail , or staffing optimization in healthcare. Users can slice and dice drift information by choosing different features to investigate drift.