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Migrate from Google BigQuery to Amazon Redshift using AWS Glue and Custom Auto Loader Framework

AWS Big Data

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytic workloads. In this post, we show you how to use AWS native services to accelerate your migration from Google BigQuery to Amazon Redshift.

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Successfully conduct a proof of concept in 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. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

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Skills and Tools Every Data Engineer Needs to Tackle Big Data

Sisense

As a company that touts the benefits of a full end-to-end BI solution, we certainly know the value of a data engineer. The data engineer’s job is to extract, clean, and normalize data, clearing the path for data scientists to explore that data and build models. Database Knowledge. Python and R.

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Unlock scalable analytics with AWS Glue and Google BigQuery

AWS Big Data

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

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Introducing Amazon Q data integration in AWS Glue

AWS Big Data

Today, we’re excited to announce general availability of Amazon Q data integration in AWS Glue. Amazon Q data integration, a new generative AI-powered capability of Amazon Q Developer , enables you to build data integration pipelines using natural language.

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How SikSin improved customer engagement with AWS Data Lab and Amazon Personalize

AWS Big Data

This post is co-written with Byungjun Choi and Sangha Yang from SikSin. From the restaurateurs’ perspective, SikSin enables restaurant partners to engage and acquire customers in order to grow their business. The SikSin Food Service team wanted to view web analytics log data by multiple dimensions, such as customer profiles and places.

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Analyze Data Faster with Google Cloud’s BigQuery Storage API

Sisense

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. We live in an era of Big Data.