Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Ascend.io

APRIL 22, 2024

This initiative is more than just an upgrade; it’s a reimagining of what a Data Automation Platform can be: dynamic, extensible, and highly intelligent. A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants. Let’s dive in!

Project 52

Project Metadata Data Pipeline Data Engineering 52

Cloudera

MARCH 17, 2023

The table format provides the necessary structure for the unstructured data that is missing in a data lake, using a schema or metadata definition, to bring it closer to a data warehouse. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Education 64

Education Unstructured Data Data Lake Data Warehouse 64

Data Engineering Podcast

SEPTEMBER 23, 2018

Using the metaphor of a museum curator carefully managing the precious resources on display and in the vaults, he discusses the various layers of an enterprise data strategy. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Expiring snapshots is a relatively cheap operation and uses metadata to determine newly unreachable files.

Bytes 59

Bytes Metadata Data Lake SQL 59

Cloudera

FEBRUARY 8, 2024

Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables. release and the matching CDW Private Cloud Data Services release, Hive also supports creating, using, and rebuilding materialized views for Iceberg table format.

Metadata 91

Metadata Data Warehouse BI AWS 91

Data Engineering Podcast

NOVEMBER 20, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130