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. Supported formats are Avro, Parquet, and ORC.

Data Lake 105

Data Lake Metadata Snapshot Recreation/Entertainment 105

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

Cloudera

SEPTEMBER 1, 2020

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. data best served through Apache Solr). See the snapshot below. What does DDE entail? Restore collection.

Snapshot 68

Snapshot Unstructured Data Dashboards Interactive 68

AWS Big Data

JANUARY 8, 2024

In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices. All these architecture patterns are integrated with Amazon Kinesis Data Streams. Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer.

Analytics 115

Analytics IoT Data-driven Snapshot 115

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 93

Data Lake Unstructured Data Management Modeling 93