Snowflake

APRIL 17, 2024

This traditional SQL-centric approach often challenged data engineers working in a Python environment, requiring context-switching and limiting the full potential of Python’s rich libraries and frameworks. To get started, explore the comprehensive API documentation , which will guide you through every step.

Data Pipeline 107

Data Pipeline Python Data Engineering Data Engineer 107

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How can we interoperate between the data domains ? How do we govern all these data products and domains ? It will be illustrated with our technical choices and the services we are using in the Google Cloud Platform.

Technology 130

Technology Architecture Google Cloud Metadata 130

Monte Carlo

NOVEMBER 14, 2023

Data orchestration tools minimize manual intervention by automating the movement of data within data pipelines. Similar to a traffic director for information, data orchestration tools gather data from various locations, organize it into a usable format, and then activate it for analysis and consumption.

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is the role of a Data Engineer? They are required to have deep knowledge of distributed systems and computer science.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. 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

Databand.ai

DECEMBER 29, 2022

Follow Ravit on LinkedIn 5) Priya Krishnan Head of Product Management, Data and AI at IBM Priya is an innovative, customer-focused, data-driven product executive with over 16 years of experience in global product management, strategy, and GTM roles to commercialize and monetize in-demand enterprise solutions.

BI 52

BI Consulting Data Science Data Governance 52

AltexSoft

JUNE 7, 2021

These pitfalls along with the need to cover an end-to-end Big Data workflow prompted the emergence of various additional services, compatible with each other. Running Spark on Kubernetes makes sense if a company plans to move the entire company techstack to the cloud-native infrastructure. Apache Hadoop ecosystem.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98