Cloudera

FEBRUARY 9, 2021

This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability. In this way, the analytic applications are able to turn the latest data into instant business insights. Cost-Effective. Low Maintenance.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Cloudera

SEPTEMBER 15, 2022

A key area of focus for the symposium this year was the design and deployment of modern data platforms. The third element in the process is the connection between the data products and the collection of analytics applications to provide business results. Ramsey International Modern Data Platform Architecture.

Data Lake 80

Data Lake Analytics Application Cloud Storage Architecture 80

Towards Data Science

APRIL 26, 2023

An open-source implementation of a Data Lake with DuckDB and AWS Lambdas A duck in the cloud. Photo by László Glatz on Unsplash In this post we will show how to build a simple end-to-end application in the cloud on a serverless infrastructure. The cloud is better. The infrastructure often gets in the way though.

Engineering 70

Engineering Data Lake AWS BI 70

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Snowflake provides a couple of ways to load data.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 40

ProjectPro

SEPTEMBER 6, 2021

Are you confused about choosing the best cloud platform for your next data engineering project ? AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. We can clean the data, convert the data, and aggregate the data using dbt so that it is ready for analysis.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

AltexSoft

OCTOBER 21, 2022

A single cluster can span across multiple data centers and cloud facilities. This allows for easy horizontal scaling — just add new servers or data centers to your existing infrastructure to handle more amount of data. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93