Remove Data Analytics Remove Data Processing Remove Data Warehouse Remove Optimization
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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The architecture consists of many layers: Rules engine – The rules engine was responsible for intercepting every incoming request.

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Enable data analytics with Talend and Amazon Redshift Serverless

AWS Big Data

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.

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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

In this post, we look into an optimal and cost-effective way of incorporating dbt within Amazon Redshift. In an optimal environment, we store the credentials in AWS Secrets Manager and retrieve them. This includes the host, port, database name, user name, and password. These SCDs identify how a row in a table changes over time.

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Setting up and Getting Started with Cloudera’s New SQL AI Assistant

Cloudera

It can help you to create, edit, optimize, fix, and succinctly summarize queries using natural language. This is a real game-changer for data analysts on all levels and will make SQL development faster, easier, and less error-prone. The optimize and the fix functionality do not need user input.

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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Monte Carlo DataData reliability delivered.

Testing 300
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Take Your SQL Skills To The Next Level With These Popular SQL Books

datapine

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.