AWS Big Data

MARCH 10, 2023

You can simplify your data strategy by running multiple workloads and applications on the same data in the same location. In this post, we show how you can build a serverless transactional data lake with Apache Iceberg on Amazon Simple Storage Service (Amazon S3) using Amazon EMR Serverless and Amazon Athena.

Data Lake 107

Data Lake Sales Data Warehouse Snapshot 107

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. It also allows you to transform, enrich, join, and aggregate data across many sources efficiently in near-real time.

Data Lake 94

Data Lake Unstructured Data Management Modeling 94

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. Key Design Goals .

Snapshot 104

Snapshot Metadata Cost-Benefit Data Architecture 104

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 . 1: Multi-function analytics .

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

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.

Data Lake 117

Data Lake Metadata Optimization Statistics 117

AWS Big Data

OCTOBER 18, 2023

The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads. Amazon Redshift is straightforward to use with self-tuning and self-optimizing capabilities. You can get faster insights without spending valuable time managing your data warehouse.

Analytics 99

Analytics Data Warehouse Testing Dashboards 99

DataKitchen

AUGUST 8, 2023

Finally, the article states that Data Observability can bring tremendous benefits and time savings by helping IT and business teams be more proactive in their data management and engineering activities. Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis.

Data Quality 130

Data Quality Testing Snapshot Reporting 130