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

AWS Big Data

This enabled our customers to see their data in a way they had never seen before. The power of QuickSight lets our customers slice and dice the data in different ways. As shown in the following screenshot, customers can filter by Review Process Type or Group Type and then take actionable next steps based on data.

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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. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 58
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Optimize queries using dataset parameters in Amazon QuickSight

AWS Big Data

Authors and readers can benefit from the faster load of analyses and dashboards for the first time using default values, as well as for later queries when data is sliced and diced using filter controls on the dashboard. Parameterized datasets can be filtered to a relatively smaller result set when loaded.

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How Newcomp Analytics partners with IBM to advance clients’ supply chain insights

IBM Big Data Hub

Left to their own devices, they had resorted to using legacy reporting tools such as Excel that required manual gathering, slicing and dicing of data. Consequently, this data was siloed, unshareable, hard to use, lacked quality and governance controls, and could not be used in automated processes.

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Ten Hidden Gems In Google Analytics: Do Smarter Web Data Analysis!

Occam's Razor

But, I'm a big believer in optimizing data access to be at the right time as defined by your decision-making/action-taking speeds inside your company. See rule #4, and video: A Big Data Imperative: Driving Big Action ] If your company can take real-time action, then real-time data becomes right-time data.

Analytics 155
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Accelerating revenue growth with real-time analytics: Poshmark’s journey

AWS Big Data

In this post, we share how Poshmark improved CX and accelerated revenue growth by using a real-time analytics solution. High-level challenge: The need for real-time analytics Previous efforts at Poshmark for improving CX through analytics were based on batch processing of analytics data and using it on a daily basis to improve CX.

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Simplify data loading into Type 2 slowly changing dimensions in Amazon Redshift

AWS Big Data

A dimension is a structure that captures reference data along with associated hierarchies, while a fact table captures different values and metrics that can be aggregated by dimensions. Dimensions provide answers to exploratory business questions by allowing end-users to slice and dice data in a variety of ways using familiar SQL commands.