The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. Because Rockset continuously syncs data from Kafka, new tweets can show up in the real-time dashboard in a matter of seconds, giving users an up-to-date view of what’s going on in Twitter.

Kafka 21

Kafka BI SQL Datasets 21

Ascend.io

FEBRUARY 12, 2023

That means data engineers consider functionality (usability, accessibility, relevance) and format (dashboards, reports, datasets) of the required data products before they start building. They gather requirements, demo early versions of data products, and iterate on them over time — just like a conventional product squad would.

Data Lake 52

Data Lake Business Analyst Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

That means data engineers consider functionality (usability, accessibility, relevance) and format (dashboards, reports, datasets) of the required data products before they start building. They gather requirements, demo early versions of data products, and iterate on them over time — just like a conventional product squad would.

Data Lake 52

Data Lake Business Analyst Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

That means data engineers consider functionality (usability, accessibility, relevance) and format (dashboards, reports, datasets) of the required data products before they start building. They gather requirements, demo early versions of data products, and iterate on them over time — just like a conventional product squad would.

Data Lake 52

Data Lake Business Analyst Data Pipeline Data 52

Monte Carlo

JUNE 14, 2022

Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Apache Spark, Trino, Flink, Presto, and Hive to safely work with the same tables, at the same time. Snowflake is going to be your unified platform for developing data applications from code to monetization. That story?

Cloud 52

Cloud Data Ingestion Government Python 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64