Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

SEPTEMBER 21, 2023

The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization. This means that Elasticsearch can be easily integrated into different modern data stacks.

Engineering 52

Engineering NoSQL Programming Language Java 52

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. This helps drive requirements and determines the right validation at the right time for the data.

IT 52

IT AWS Software Engineer Software Engineering 52

AltexSoft

MARCH 14, 2023

Data uses Here comes why you need this whole MDS thing in the first place — the data use component, or how the data is actually utilized. There are two main areas of use within this component: the first is data analytics and business intelligence and the second is data science.

IT 59

IT Data Warehouse Data Governance Data Lake 59