AWS Big Data

MARCH 10, 2023

Apache Iceberg overview Iceberg is an open-source table format that brings the power of SQL tables to big data files. It enables ACID transactions on tables, allowing for concurrent data ingestion, updates, and queries, all while using familiar SQL. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 3: Open Performance.

Metadata 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

Alation

JULY 28, 2022

What Are the Biggest Drivers of Cloud Data Warehousing? It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. There are tools to replicate and snapshot data, plus tools to scale and improve performance.”

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Non-blocking automatic table services (for example, compaction) that don’t impact writers or readers.

Data Lake 116

Data Lake Metadata Optimization Statistics 116

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Testing 130

Testing Data Governance Data Quality Data-driven 130