Category: AWS Big Data

This is a guest post by Christa Pierson and Jon Fearer at OrthoFi. OrthoFi is an orthodontic industry leader in revenue cycle management (RCM), and has partnered with more than 550 orthodontic practices across the country, delivering an end-to-end platform that enables orthodontists to bring on more patients and run their businesses more effectively. To […]

We recently announced Amazon FinSpace, a fully-managed data management and analytics service that makes it easy to store, catalog, and prepare financial industry data at scale, reducing the time it takes for financial services industry (FSI) customers to find and access all types of financial data for analysis from months to minutes. Financial services organizations […]

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. Analysts are building complex data transformation pipelines that include multiple steps for data preparation and cleansing. However, analysts may want a simpler orchestration mechanism with a graphical user interface that […]

Presto is an open-source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. Presto was designed and written from the ground up for interactive analytics, and approaches the speed of commercial data warehouses while scaling to the size of organizations like Facebook. Running Presto […]

AWS provides many ways to optimize your workloads and save on costs. For example, services like AWS Cost Explorer and AWS Trusted Advisor provide cost savings recommendations to help you optimize your AWS environments. However, you may also want to estimate cost savings when comparing Amazon Elastic Compute Cloud (Amazon EC2) Spot to On-Demand Instances. […]

AWS Glue is fully managed service that makes it easier for you to extract, transform, and load (ETL) data for analytics. You can easily create ETL jobs to connect to backend data sources. There are several natively supported data sources, but what if you need to extract data from an unsupported data source? What if […]

This blog post was last updated July, 2022 to update the new version of the connector and details on how to push down queries to Google BigQuery. The cloud is often seen as advantageous for data lakes because of better security, faster time to deployment, better availability, more frequent feature and functionality updates, more elasticity, […]

Today, with AWS Glue DataBrew, data analysts and data scientists can easily access and visually explore any amount of data across their organization directly from their Amazon Simple Storage Service (Amazon S3) data lake, Amazon Redshift data warehouse, and Amazon Aurora and Amazon Relational Database Service (Amazon RDS) databases. Customers can choose from over 250 […]

Apache HBase is an open-source, NoSQL database that you can use to achieve low latency random access to billions of rows. Starting with Amazon EMR 5.2.0, you can enable HBase on Amazon Simple Storage Service (Amazon S3). With HBase on Amazon S3, the HBase data files (HFiles) are written to Amazon S3, enabling data lake […]

A common challenge ETL and big data developers face is working with data files that don’t have proper name header records. They’re tasked with renaming the columns of the data files appropriately so that downstream application and mappings for data load can work seamlessly. One example use case is while working with ORC files and […]