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. Clustering data for better data colocation using z-ordering.

Data Lake 130

Data Lake Metadata Statistics Optimization 130

AWS Big Data

AUGUST 2, 2023

Using existing analytics tools such as Amazon Athena and Amazon QuickSight an organization can gain insight into its estimated carbon footprint. The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint.

Data Lake 97

Data Lake Measurement Visualization Data Architecture 97

AWS Big Data

AUGUST 1, 2024

Success criteria alignment by all stakeholders (producers, consumers, operators, auditors) is key for successful transition to a new Amazon Redshift modern data architecture. The success criteria are the key performance indicators (KPIs) for each component of the data workflow. The following figure shows a daily usage KPI.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

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. Data streaming enables you to ingest data from a variety of databases across various systems.

Data Lake 121

Data Lake Unstructured Data Management Snapshot 121

AWS Big Data

APRIL 3, 2024

By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes. He focuses on modern data architectures and helping customers accelerate their cloud journey with serverless technologies.

Data Quality 118

Data Quality Visualization Metadata Metrics 118

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. Over the years, he has helped multiple customers on data platform transformations across industry verticals. His core area of expertise include Technology Strategy, Data Analytics, and Data Science.

Data Lake 101

Data Lake Testing Snapshot Big Data 101

AWS Big Data

FEBRUARY 9, 2023

With scheduled flows, you can choose either full or incremental data transfer: With full transfer, Amazon AppFlow transfers a snapshot of all records at the time of the flow run from the source to the destination. Amit Shah is a cloud based modern data architecture expert and currently leading AWS Data Analytics practice in Atos.

Data Warehouse 104

Data Warehouse Data-driven Snapshot Testing 104

AWS Big Data

OCTOBER 18, 2023

Many customers migrate their data warehousing workloads to Amazon Redshift and benefit from the rich capabilities it offers, such as the following: Amazon Redshift seamlessly integrates with broader data, analytics, and AI or machine learning (ML) services on AWS , enabling you to choose the right tool for the right job.

Analytics 111

Analytics Data Warehouse Dashboards Testing 111

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.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

AWS Big Data

MARCH 28, 2024

Amazon EMR stands as a dynamic force in the cloud, delivering unmatched capabilities for organizations seeking robust big data solutions. Its seamless integration, powerful features, and adaptability make it an indispensable tool for navigating the complexities of data analytics and ML on AWS.

Optimization 113

Optimization IT Big Data Data Processing 113

Cloudera

DECEMBER 3, 2024

Apache Iceberg, together with the REST Catalog, dramatically simplifies the enterprise data architecture, reducing the Time to Value, Time to Market, and overall TCO, and driving greater ROI. It provides real time metadata access by directly integrating with the Iceberg-compatible metastore.

Metadata 84

Metadata Data Warehouse ROI Machine Learning 84

DataKitchen

AUGUST 8, 2023

Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis. This is especially true regarding our one-to-many, producer-to-consumer relationships on our data architecture. Are problems with data tests? Which report tab is wrong? When did it last run? Did it fail?

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.

Testing 130

Testing Data Governance Data Quality Data-driven 130