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Analyzing Data from Multiple Sources: The Key to More Powerful Insights

Sisense

Machine learning and predictive modeling allowed the company to use complex historical warranty claim and cost information, previous and new product attributes, and forecasting data to create a predictive data model for future warranty costs. With a tool like Sisense, it changes the game altogether.”.

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

AWS Big Data

In this post, we discuss how we use QuickSight to deliver powerful HR analytics to over 3,000 customers and 43,000 users while forecasting savings of 84% year-over-year as compared to our legacy reporting solutions. The power of QuickSight lets our customers slice and dice the data in different ways.

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Do I Need Both BI Tools and Augmented Analytics?

Smarten

Recent studies have focused on the trends in business intelligence and augmented analytics, predicting that businesses will grow analytics within the enterprise with: Augmented Analytics to enable non-technical business users to create sophisticated data models. Predictive Modeling to support business needs, forecast, and test theories.

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

DataRobot Blog

How do you track the integrity of a machine learning model in production? Model Observability can help. By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Model Observability Features.

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The Complete Digital Analytics Ecosystem: How To Win Big

Occam's Razor

You need to slice! You need to dice! Repeat after me: Slice, dice, drill!! You have to get good at some predictive analysis and forecasting (basic kinds), being able to talk to other teams, working with Finance in particular, understanding macro business trends etc. You need to drill! Good stuff, great outcomes.

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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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What is OLAP?

Jedox

We explain what lies behind OLAP, what cubes have to do with it and what makes the technology so powerful for modern planning, budgeting, and forecasting. To get an idea of how it works, the cube works really well as a model. In this blog post, we’ll look at the definition of OLAP as well as an overview of the technology.

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