Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? 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. Despite Hadoop’s parallel and distributed processing, compute was a limited resource as well.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Ascend.io

MAY 31, 2023

Table of Contents The Common Threads: Ingest, Transform, Share Before we explore the differences between the ETL process and a data pipeline , let’s acknowledge their shared DNA. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

AltexSoft

SEPTEMBER 21, 2023

Accessible via a unified API, these new features enhance search relevance and are available on Elastic Cloud. 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.

Engineering 52

Engineering NoSQL Programming Language Java 52

Ascend.io

MARCH 17, 2023

Kubernetes Problem As cloud applications arose, the infrastructure of virtual machines became more and more similar. Containers sequester memory, CPU, processing space, and file systems from the underlying hardware to securely power applications. Value Catching data problems in real-time avoids costly reruns and delays.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

Kubernetes Problem As cloud applications arose, the infrastructure of virtual machines became more and more similar. Containers sequester memory, CPU, processing space, and file systems from the underlying hardware to securely power applications. Value Catching data problems in real-time avoids costly reruns and delays.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

phData: Data Engineering

JANUARY 3, 2022

You may need to build another data center or work with a cloud provider to have another set of infrastructure to failover to. Many companies go with cloud providers to ensure availability, reduce infrastructure management, and reduce their security footprint. This could be on-premises servers or cloud providers.

IT 52

IT AWS Software Engineer Software Engineering 52

Snowflake

MARCH 27, 2023

Introducing CARTO Workflows Snowflake’s powerful data ingestion and transformation features help many data engineers and analysts who prefer SQL. Workflows automates not only geospatial processes, but other data workflows as well.

Generalist 52

Generalist Raw Data Business Analyst SQL 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59