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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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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting. This will be your OLTP data store for transactional data. version cluster. version cluster.

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A hybrid approach in healthcare data warehousing with Amazon Redshift

AWS Big Data

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

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Data Modeling 101: OLTP data modeling, design, and normalization for the cloud

erwin

I was pricing a data warehousing project with just 4 TB of data – small by today’s standards. I chose “OnDemand” for up to 64 virtual CPUs and 448 GB of memory, since this data warehouse wanted to leverage in-memory processing. So that’s $136,000 per year just to run this one data warehouse in the cloud.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Are you seeing any specific issues around the insurance industry at the moment that should concern CDAOs?

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The Key to Faster Impact Analysis: Automated Data Lineage

Octopai

To make changes to a system, report, or process, BI developers must first perform impact analysis in order to gauge the potential impact of making such a change on the rest of the environment. With this problem solved, the Department of Transportation sent a memo to insurance companies informing them of the impending change and moved along.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.