AWS Big Data

JULY 29, 2024

They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources. Data lakes provide a unified repository for organizations to store and use large volumes of data.

Metadata 109

Metadata Snapshot Data Lake Metrics 109

Cloudera

AUGUST 21, 2024

This year, we’re excited to share that Cloudera’s Open Data Lakehouse 7.1.9 release was named a finalist under the category of Business Intelligence and Data Analytics. The root of the problem comes down to trusted data. Open Data Lakehouse also offers expanded support for Python 3.10 and RHEL 9.1,

Snapshot 69

Snapshot Unstructured Data Data Architecture Data Warehouse 69

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 115

Analytics IoT Data-driven Snapshot 115

Cloudera

SEPTEMBER 1, 2020

It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e.

Snapshot 71

Snapshot Unstructured Data Dashboards Interactive 71

AWS Big Data

OCTOBER 3, 2023

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. target_iceberg_add_files/metadata/.

Data Lake 107

Data Lake Metadata Snapshot Recreation/Entertainment 107

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 119

Data Lake Data Processing Metadata Snapshot 119

AWS Big Data

MARCH 25, 2024

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For building such a data store, an unstructured data store would be best.

Data Lake 94

Data Lake Unstructured Data Management Snapshot 94