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 97

Data Pipeline Python Data Engineering Data Engineer 97

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. The next problem will be the diversity of these mini data platforms (because of the configuration) and you even go deeper in problems with managing different technologies or version.

Architecture 130

Architecture Technology Google Cloud Metadata 130

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

Monte Carlo

NOVEMBER 14, 2023

This is the world that data orchestration tools aim to create. Data orchestration tools minimize manual intervention by automating the movement of data within data pipelines. According to one Redditor on r/dataengineering, “Seems like 99/100 data engineering jobs mention Airflow.”

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

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

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. It also provides tools for statistics, creating ML pipelines, model evaluation, and more. It’s also important to understand the core principles behind Hadoop.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Databand.ai

DECEMBER 29, 2022

Follow Sudhir on LinkedIn 13) Benjamin Rogojan Data Science And Data Engineering Consultant at Acheron Analytics Benjamin is a data science and data engineering consultant with nearly a decade of experience working with companies like Healthentic, Facebook, and Acheron Analytics.

BI 52

BI Consulting Data Science Data Governance 52