AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 126

Optimization Snapshot Data Lake Metadata 126

AWS Big Data

JANUARY 8, 2024

It can receive the events from an input Kinesis data stream and route the resulting stream to an output data stream. State snapshot in Amazon S3 – You can store the state snapshot in Amazon S3 for tracking. You can create a stateful functions cluster with Apache Flink based on your application business logic.

Analytics 134

Analytics IoT Data-driven Snapshot 134

Corinium

APRIL 25, 2019

And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. And more recently, we have also seen innovation with IOT (Internet Of Things). In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

NOVEMBER 6, 2024

Second, because traditional data warehousing approaches are unable to keep up with the volume, velocity, and variety of data, engineering teams are building data lakes and adopting open data formats such as Parquet and Apache Iceberg to store their data.

Metadata 115

Metadata Data Lake Management Internet of Things 115

AWS Big Data

DECEMBER 13, 2023

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Internet-of-Things [ IoT] devices, system telemetry data, or clickstream data) from a busy website or application.

Data Warehouse 116

Data Warehouse Snapshot Data Processing Internet of Things 116

AWS Big Data

DECEMBER 19, 2024

Data lakes were originally designed to store large volumes of raw, unstructured, or semi-structured data at a low cost, primarily serving big data and analytics use cases. Enabling automatic compaction on Iceberg tables reduces metadata overhead on your Iceberg tables and improves query performance.

Data Lake 52

Data Lake IoT Metadata Testing 52

AWS Big Data

AUGUST 1, 2024

We can determine the following are needed: An open data format ingestion architecture processing the source dataset and refining the data in the S3 data lake. This requires a dedicated team of 3–7 members building a serverless data lake for all data sources. Vijay Bagur is a Sr.

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113