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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Cloudera Data Warehouse Demonstrates Best-in-Class Cloud-Native Price-Performance

Cloudera

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

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Enable business users to analyze large datasets in your data lake with Amazon QuickSight

AWS Big Data

This blog post is co-written with Ori Nakar from Imperva. Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. Imperva’s data lake has a few dozen different datasets, in the scale of petabytes.

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Deriving Value from Data Lakes with AI

Sisense

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. Let’s talk about AI and machine learning (ML). AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information.

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Data Modeling 301 for the cloud: data lake and NoSQL data modeling and design

erwin

This blog is based upon a recent webcast that can be viewed here. For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. As with the part 1 and part 2 of this data modeling blog series, the cloud is not nirvana.

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Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

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Data Modeling 201 for the cloud: designing databases for data warehouses

erwin

This blog is based upon webcast which can be watched here. Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts.