AWS Big Data

JULY 17, 2024

sink: - opensearch: # Provide an AWS OpenSearch Service domain endpoint hosts: [ "[link]. > arn: "arn:aws:kafka:us-east-1: >:cluster/ >/ >" processor: - parse_json: sink: - opensearch: # Provide an AWS OpenSearch Service domain endpoint hosts: [ "[link] > us-east-1.es.amazonaws.com"

Analytics 115

Analytics IoT Dashboards Data Lake 115

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. This native feature of Amazon Redshift uses massive parallel processing (MPP) to load objects directly from data sources into Redshift tables. Sudipta Bagchi is a Sr.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

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. This solution uses Amazon Aurora MySQL hosting the example database salesdb.

Data Warehouse 116

Data Warehouse Snapshot Data Processing Internet of Things 116

Sisense

OCTOBER 6, 2020

When these systems connect with external groups — customers, subscribers, shareholders, stakeholders — even more data is generated, collected, and exchanged. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. First, data isn’t created in a uniform, consistent format.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

Data Lake 98

Data Lake Data Analytics Analytics Data Processing 98