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Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

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Fire Your Super-Smart Data Consultants with DataOps

DataKitchen

DataOps improves the robustness, transparency and efficiency of data workflows through automation. For example, DataOps can be used to automate data integration. Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake.

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Automate schema evolution at scale with Apache Hudi in AWS Glue

AWS Big Data

In the data analytics space, organizations often deal with many tables in different databases and file formats to hold data for different business functions. Apache Hudi supports ACID transactions and CRUD operations on a data lake. You don’t alter queries separately in the data lake. and save it.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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Dive deep into AWS Glue 4.0 for Apache Spark

AWS Big Data

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. We observed that our TPC-DS tests on Amazon S3 had a total job runtime on AWS Glue 4.0

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Automate the archive and purge data process for Amazon RDS for PostgreSQL using pg_partman, Amazon S3, and AWS Glue

AWS Big Data

This post proposes an automated solution by using AWS Glue for automating the PostgreSQL data archiving and restoration process, thereby streamlining the entire procedure. You can create an AWS Cloud9 environment in one of the private subnets available in your AWS account to set up test data in Amazon RDS.

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Handle UPSERT data operations using open-source Delta Lake and AWS Glue

AWS Big Data

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities. option("header",True).schema(schema).load("s3://"+