AWS Big Data Blog

Tag: Analytics

Detect and handle data skew on AWS Glue

AWS Glue is a fully managed, serverless data integration service provided by Amazon Web Services (AWS) that uses Apache Spark as one of its backend processing engines (as of this writing, you can use Python Shell, Spark, or Ray). Data skew occurs when the data being processed is not evenly distributed across the Spark cluster, […]

How the GoDaddy data platform achieved over 60% cost reduction and 50% performance boost by adopting Amazon EMR Serverless

This is a guest post co-written with Brandon Abear, Dinesh Sharma, John Bush, and Ozcan IIikhan from GoDaddy. GoDaddy empowers everyday entrepreneurs by providing all the help and tools to succeed online. With more than 20 million customers worldwide, GoDaddy is the place people come to name their ideas, build a professional website, attract customers, […]

Dimensional modeling in Amazon Redshift

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model. Amazon Redshift […]

How CyberSolutions built a scalable data pipeline using Amazon EMR Serverless and the AWS Data Lab

This post is co-written by Constantin Scoarță and Horațiu Măiereanu from CyberSolutions Tech. CyberSolutions is one of the leading ecommerce enablers in Germany. We design, implement, maintain, and optimize award-winning ecommerce platforms end to end. Our solutions are based on best-in-class software like SAP Hybris and Adobe Experience Manager, and complemented by unique services that […]

Automate replication of relational sources into a transactional data lake with Apache Iceberg and AWS Glue

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history. According to a study, the […]

Choose the k-NN algorithm for your billion-scale use case with OpenSearch

April 2024: This post was reviewed for accuracy. February 2023: This post was reviewed and updated for accuracy of the code. When organizations set out to build machine learning (ML) applications such as natural language processing (NLP) systems, recommendation engines, or search-based systems, often times k-Nearest Neighbor (k-NN) search will be used at some point […]

Interactively develop your AWS Glue streaming ETL jobs using AWS Glue Studio notebooks

Enterprise customers are modernizing their data warehouses and data lakes to provide real-time insights, because having the right insights at the right time is crucial for good business outcomes. To enable near-real-time decision-making, data pipelines need to process real-time or near-real-time data. This data is sourced from IoT devices, change data capture (CDC) services like […]

Example of an embedded dashboard

Top Amazon QuickSight features launched in Q2 2022

Amazon QuickSight is a serverless, cloud-based business intelligence (BI) service that brings data insights to your teams and end-users through machine learning (ML)-powered dashboards and data visualizations, which can be accessed via QuickSight or embedded in apps and portals that your users access. This post shares the top QuickSight features and updates launched in Q2 […]

Disaster recovery considerations with Amazon EMR on Amazon EC2 for Spark workloads

Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning (ML) applications using open-source analytics frameworks such as Apache Spark, Apache Hive, and Presto. Amazon EMR launches all nodes for a given cluster in the same Amazon Elastic Compute Cloud (Amazon EC2) Availability Zone […]