AWS Big Data Blog
Category: Analytics
How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform
This blog post was last reviewed May, 2022. This is a joint blog post co-authored with Anu Jain, Graham Person, and Paul Conroy from JP Morgan Chase. Most modern organizations recognize that their data benefits their entire enterprise. Data has value to the individual business process that produces it, but data’s additional potential can be […]
Read MoreUse HyperLogLog for trend analysis with Amazon Redshift
Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL. Amazon Redshift offers up to three times better price performance than any other cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of […]
Read MoreEffective data lakes using AWS Lake Formation, Part 3: Using ACID transactions on governed tables
Data lakes on Amazon Simple Storage Service (Amazon S3) have become the default repository for all enterprise data and serve as common choice for a large number of users querying from a variety of analytics and ML tools. Often times you want to ingest data continuously into the data lake from multiple sources and query against the […]
Read MoreUse Grok patterns in AWS Glue to process streaming data into Amazon Elasticsearch Service
September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Recently, we launched AWS Glue custom connectors for Amazon OpenSearch Service, which provides the capability to ingest data into Amazon OpenSearch Service with just a few clicks. You can now use Amazon OpenSearch Service as a data store for your […]
Read MoreHow Digital Infuzion solves the challenge of large-scale scientific data collaboration with Amazon Quicksight
This is a guest post by Digital Infuzion. In their own words, “Digital Infuzion (DIFZ), a leader in information technology, helps solve complex challenges related to genomics, health, and biomedical data, while collaborating with partners including the J. Craig Venter Institute, Gryphon Scientific, ICF International, and others engaged in scientific research. Together, we create novel […]
Read MoreHow OrthoFi delivers better insights for customers with Amazon Redshift and AWS Glue
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 […]
Read MoreOrchestrate AWS Glue DataBrew jobs using Amazon Managed Workflows for Apache Airflow
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 […]
Read MoreEnrich your data stream asynchronously using Amazon Kinesis Data Analytics for Apache Flink
Streaming data into or out of a data system must be fast. One of the most expensive pieces of any streaming system is the I/O of the system: reading from the streaming layer using Apache Kafka or Amazon Kinesis, reading a file, writing to an Amazon Simple Storage Service (Amazon S3) data lake, or communicating […]
Read MoreAmazon EMR introduces EMR runtime for Presto, providing a 2.6 times speedup
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 […]
Read MoreAmazon Redshift announces general availability of support for JSON and semi-structured data processing
At AWS re:Invent 2020, we announced the preview of native support for JSON and semi-structured data in Amazon Redshift. This includes a new data type, SUPER, which allows you to store JSON and other semi-structured data in Amazon Redshift tables, and support for the PartiQL query language, which allows you to seamlessly query and process […]
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