AWS Big Data Blog

Category: Intermediate (200)

Scale your AWS Glue for Apache Spark jobs with new larger worker types G.4X and G.8X

Hundreds of thousands of customers use AWS Glue, a serverless data integration service, to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue for Apache Spark jobs work with your code and configuration of the number of data processing units (DPU). Each DPU provides 4 vCPU, 16 GB memory, […]

New scatter plot options in Amazon QuickSight to visualize your data

Are you looking to understand the relationships between two numerical variables? Scatter plots are a powerful visual type that allow you to identify patterns, outliers, and strength of relationships between variables. In this post, we walk you through the newly launched scatter plot features in Amazon QuickSight, which will help you take your correlation analysis […]

Build efficient, cross-Regional, I/O-intensive workloads with Dask on AWS

Welcome to the era of data. The sheer volume of data captured daily continues to grow, calling for platforms and solutions to evolve. Services such as Amazon Simple Storage Service (Amazon S3) offer a scalable solution that adapts yet remains cost-effective for growing datasets. The Amazon Sustainability Data Initiative (ASDI) uses the capabilities of Amazon […]

Build, deploy, and run Spark jobs on Amazon EMR with the open-source EMR CLI tool

Today, we’re pleased to introduce the Amazon EMR CLI, a new command line tool to package and deploy PySpark projects across different Amazon EMR environments. With the introduction of the EMR CLI, you now have a simple way to not only deploy a wide range of PySpark projects to remote EMR environments, but also integrate […]

Compose your ETL jobs for MongoDB Atlas with AWS Glue

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data. This is driven by the need to centralize and integrate data coming from disparate sources. At the same […]

Data load made easy and secure in Amazon Redshift using Query Editor V2

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to analyze all your data efficiently and securely. Users such as data analysts, database developers, and data scientists use SQL to analyze their data in Amazon Redshift data warehouses. Amazon Redshift provides a web-based Query Editor V2 in […]

What’s new with Amazon MWAA support for Apache Airflow version 2.4.3

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that makes it simple to set up and operate end-to-end data pipelines in the cloud at scale. Amazon MWAA supports multiple versions of Apache Airflow (v1.10.12, v2.0.2, and v2.2.2). Earlier in 2023, we added support for Apache Airflow v2.4.3 […]

Real-time anomaly detection via Random Cut Forest in Amazon Managed Service for Apache Flink

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Real-time anomaly detection describes a use case to detect and flag unexpected behavior in streaming data as it occurs. Online machine learning (ML) algorithms are popular for […]

Monitor and optimize cost on AWS Glue for Apache Spark

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. One of […]

How Dafiti made Amazon QuickSight its primary data visualization tool

This is a guest post by Valdiney Gomes, Hélio Leal, and Flávia Lima from Dafiti. Data and its various uses is increasingly evident in companies, and each professional has their preferences about which technologies to use to visualize data, which isn’t necessarily in line with the technological needs and infrastructure of a company. At Dafiti, […]