AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

AWS Big Data

AUGUST 2, 2023

In this blog, we will walk through how we can apply existing enterprise data to better understand and estimate Scope 1 carbon footprint using Amazon Simple Storage Service (S3) and Amazon Athena , a serverless interactive analytics service that makes it easy to analyze data using standard SQL.

Data Lake 73

Data Lake Measurement Visualization Data Architecture 73

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.

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Data Lake Metadata Optimization Statistics 114

AWS Big Data

MARCH 28, 2023

This post is designed to be implemented for a real customer use case, where you get full snapshot data on a daily basis. Vijay Velpula is a Data Architect with AWS Professional Services. He helps customers implement Big Data and Analytics Solutions.

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Data Lake Testing Snapshot Sales 72

AWS Big Data

MARCH 28, 2024

With these frameworks and related open-source projects, you can process data for analytics purposes and BI workloads. Amazon EMR lets you transform and move large amounts of data in and out of other AWS data stores and databases, such as Amazon S3 and Amazon DynamoDB.

Optimization 81

Optimization IT Big Data Data Processing 81

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

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Data Lake Dashboards Metrics Metadata 84

DataKitchen

AUGUST 8, 2023

In the article, Melody Chien notes that Data Observability is a practice that extends beyond traditional monitoring and detection, providing robust, integrated visibility over data and data landscapes. It alerts data and analytics leaders to issues with their data before they multiply. When did it last run?

Data Quality 130

Data Quality Testing Snapshot Reporting 130

DataKitchen

JANUARY 23, 2023

To capture a more complete picture of the data’s journey, it is important to have a DataOps Observability system in place. Data lineage is static and often lags by weeks or months. Data lineage is often considered static because it is typically based on snapshots of data and metadata taken at a specific time.

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Testing Data Governance Data Quality Data-driven 130