Category: AWS Glue

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning (ML), and application development. In AWS Glue, you can use Apache Spark, an open-source, distributed processing system for your data integration tasks and big data workloads. Apache Spark utilizes in-memory caching and optimized […]

AWS SDK for pandas is an open-source library that extends the popular Python pandas library, enabling you to connect to AWS data and analytics services using pandas data frames. We’ve seen customers use the library in combination with pandas for both data engineering and AI workloads. Although pandas data frames are simple to use, they […]

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. Today, AWS Glue processes customer jobs using either Apache Spark’s distributed processing engine for large workloads or Python’s single-node processing engine for smaller workloads. Customers […]

This is a guest post co-written with Ankit Jhalaria from GoDaddy. GoDaddy is empowering 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 idea, build a professional website, attract customers, and manage their work. GoDaddy is […]

Organizations are placing a high priority on data integration, especially to support analytics, machine learning (ML), business intelligence (BI), and application development initiatives. Data is growing exponentially and is generated by increasingly diverse data sources. Data integration becomes challenging when processing data at scale and the inherent heavy lifting associated with infrastructure required to manage […]

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to scan data in the background, so you can focus on using the data to make better intelligent decisions. You may also have data in data warehouses such as Snowflake and want the ability to discover the […]

In this post, we take the data mesh design discussed in Design a data mesh architecture using AWS Lake Formation and AWS Glue, and demonstrate how to initialize data domain accounts to enable managed sharing; we also go through how we can use an event-driven approach to automate processes between the central governance account and […]

This is a guest blog post co-written with Addison Higley and Ramzi Yassine from Hudl. Hudl Agile Sports Technologies, Inc. is a Lincoln, Nebraska based company that provides tools for coaches and athletes to review game footage and improve individual and team play. Its initial product line served college and professional American football teams. Today, […]

As the industry grows with more data volume, big data analytics is becoming a common requirement in data analytics and machine learning (ML) use cases. Data comes from many different sources in structured, semi-structured, and unstructured formats. For semi-structured data, one of the most common lightweight file formats is JSON. However, due to the complex […]

Many organizations build data lakes on Amazon Simple Storage Service (Amazon S3) using a modern architecture for a scalable and cost-effective solution. Open-source storage formats like Parquet and Avro are commonly used, and data is stored in these formats as immutable files. As the data lake is expanded to additional use cases, there are still […]