Remove Analytics Remove Data Integration Remove Data Lake Remove Interactive
article thumbnail

Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 102
article thumbnail

Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. a new version of AWS Glue that accelerates data integration workloads in AWS.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started

AWS Big Data

AWS Glue is a serverless, scalable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources. AWS Glue provides an extensible architecture that enables users with different data processing use cases. as follows: # Use Glue version 3.0

Data Lake 111
article thumbnail

With a zero-ETL approach, AWS is helping builders realize near-real-time analytics

AWS Big Data

In case the data sources change, data engineers have to manually make changes in their code and deploy it again. Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules.

article thumbnail

Building Best-in-Class Enterprise Analytics

Speaker: Anthony Roach, Director of Product Management at Tableau Software, and Jeremiah Morrow, Partner Solution Marketing Director at Dremio

Tableau works with Strategic Partners like Dremio to build data integrations that bring the two technologies together, creating a seamless and efficient customer experience. As a result of a strategic partnership, Tableau and Dremio have built a native integration that goes well beyond a traditional connector.

article thumbnail

Data governance in the age of generative AI

AWS Big Data

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

article thumbnail

Simplifying data processing at Capitec with Amazon Redshift integration for Apache Spark

AWS Big Data

Amazon Redshift offers seamless integration with Apache Spark, allowing you to easily access your Redshift data on both Amazon Redshift provisioned clusters and Amazon Redshift Serverless. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. options(**read_config).option("query",