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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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Accelerate your data warehouse migration to Amazon Redshift – Part 7

AWS Big Data

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

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Take Your SQL Skills To The Next Level With These Popular SQL Books

datapine

With a MySQL dashboard builder , for example, you can connect all the data with a few clicks. A host of notable brands and retailers with colossal inventories and multiple site pages use SQL to enhance their site’s structure functionality and MySQL reporting processes. These businesses include eBay, Autotrader, and Amazon.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Amazon Redshift is straightforward to use with self-tuning and self-optimizing capabilities. Analyze the assessment report and address the action items.

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How Gilead used Amazon Redshift to quickly and cost-effectively load third-party medical claims data

AWS Big Data

Because Gilead is expanding into biologics and large molecule therapies, and has an ambitious goal of launching 10 innovative therapies by 2030, there is heavy emphasis on using data with AI and machine learning (ML) to accelerate the drug discovery pipeline. This data volume is expected to increase monthly and is fully refreshed each month.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning. With these insights, teams have the visibility to make data integration pipelines more efficient.

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