ProjectPro

JUNE 6, 2025

Companies need ETL engineers to ensure data is extracted, transformed, and loaded efficiently, enabling accurate insights and decision-making. Source: LinkedIn The rise of cloud computing has further accelerated the need for cloud-native ETL tools , such as AWS Glue , Azure Data Factory , and Google Cloud Dataflow.

Data Engineer 40

Data Engineer Data Engineering Engineering ETL Tools 40

Data Engineering Podcast

MAY 26, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Systems 130

Systems Data Lake High Quality Data Google Cloud 130

Data Engineering Podcast

JULY 17, 2022

Shipyard]([link] Shipyard is an orchestration platform that helps data teams build out solid data operations from the get-go by connecting data tools and streamlining data workflows.

Data Management 130

Data Management Management Metadata MongoDB 130

ProjectPro

JUNE 6, 2025

Source- Building A Serverless Pipeline using AWS CDK and Lambda ETL Data Integration From GCP Cloud Storage Bucket To BigQuery This data integration project will take you on an exciting journey, focusing on extracting, transforming, and loading raw data stored in a Google Cloud Storage (GCS) bucket into BigQuery using Cloud Functions.

Data Integration 40

Data Integration Project Hospitality Data Lake 40

ProjectPro

JUNE 6, 2025

Apache Beam Apache Beam is an open-source data processing framework that allows you to build batch and stream data processing pipelines. It supports multiple execution engines, including Apache Flink and Google Cloud Dataflow, and provides a Python SDK for ETL development.

Python 40

Python ETL Tools Data Warehouse Programming Language 40

ProjectPro

JUNE 6, 2025

This storage layer is the backbone of the Fabric ecosystem, offering a unified location to store all organizational data while seamlessly integrating with various Microsoft platforms, Amazon S3, and potentially Google Cloud Platform.

Database-centric 40

Database-centric BI Pipeline-centric Data Lake 40

ProjectPro

JUNE 6, 2025

Machine Learning engineers are often required to collaborate with data engineers to build data workflows. As a Google research scientist, one must work on cutting-edge machine intelligence and machine learning systems and generate solutions for real-world, large-scale challenges.

Machine Learning 49

Machine Learning Engineering Algorithm Programming Language 49

Hevo

AUGUST 16, 2024

This blog explores the world of open source data orchestration tools, highlighting their importance in managing and automating complex data workflows. From Apache Airflow to Google Cloud Composer, we’ll walk you through ten powerful tools to streamline your data processes, enhance efficiency, and scale your growing needs.

Google Cloud 52

Google Cloud Data Workflow Data Data Engineer 52

ProjectPro

JUNE 6, 2025

A data science pipeline represents a systematic approach to collecting, processing, analyzing, and visualizing data for informed decision-making. Data science pipelines are essential for streamlining data workflows, efficiently handling large volumes of data, and extracting valuable insights promptly.

Data Science 40

Data Science Building AWS Data Lake 40

ProjectPro

JUNE 6, 2025

Experience with Cloud Platforms and Tools Cloud platforms like AWS , Google Cloud, and Azure offer robust environments for deploying and scaling ML models. Understanding cloud services such as AWS SageMaker, Google AI Platform, or Azure Machine Learning can significantly enhance your ability to manage ML workflows.

Programming 40

Programming Pipeline-centric Machine Learning Database-centric 40

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Azure DevOps.

Consulting 121

Consulting Machine Learning Government Data Science 121

ProjectPro

JUNE 6, 2025

This makes Python a natural fit for ETL workflows across both fast-moving startups and large-scale enterprise data teams. Here’s why building ETL pipelines with Python is a no-brainer - Python makes it easy to write and maintain complex ETL data workflows.

Python 40

Python Building PostgreSQL Raw Data 40

ProjectPro

JUNE 6, 2025

This growth is due to the increasing adoption of cloud-based data integration solutions such as Azure Data Factory. If you have heard about cloud computing , you would have heard about Microsoft Azure as one of the leading cloud service providers in the world, along with AWS and Google Cloud.

Data Lake 60

Data Lake Metadata SQL Datasets 60

Monte Carlo

FEBRUARY 25, 2025

Data engineering design patterns are repeatable solutions that help you structure, optimize, and scale data processing, storage, and movement. They make data workflows more resilient and easier to manage when things inevitably go sideways. Common solutions include AWS S3 , Azure Data Lake , and Google Cloud Storage.

Designing 52

Designing Data Engineer Data Engineering Engineering 52

Ascend.io

DECEMBER 21, 2022

By harnessing the power of Ascend and Snowflake, data teams can now ingest any data from any location, and in just minutes begin releasing entirely new data products. “We’re here to help our customers focus on the data transformation that produces real value, not just busywork.

Data Ingestion 52

Data Ingestion Google Cloud Data Lake Cloud 52

Monte Carlo

NOVEMBER 14, 2023

Let’s take a look at 11 other data orchestration tools challenging Airflow’s seat at the table. But even as the modern data stack continues to evolve, Airflow maintains its title as a perennial data orchestration favorite—and for good reason. First things first—what’s Airflow?

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

RandomTrees

SEPTEMBER 17, 2024

This integration ensures that data governance is cohesive and consistent across all aspects of the data workflow. Unity Catalog vs. Other Data Catalog Tools: A Simple Comparison 1. Integration: Unity Catalog works easily with Databricks and ideal for those using Databricks for data & AI.

Data Governance 52

Data Governance Government Metadata Machine Learning 52

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineer Data Engineering Engineering 52

Monte Carlo

SEPTEMBER 20, 2022

Here’s how Prefect , Series B startup and creator of the popular data orchestration tool, harnessed the power of data observability to preserve headcount, improve data quality and reduce time to detection and resolution for data incidents. This left Dylan’s team with a gap to fill.

Big Data 52

Big Data Data Warehouse Data Governance Data 52

Monte Carlo

JUNE 14, 2023

Apache Spark – Labeled as a unified analytics engine for large scale data processing, many leverage this open source solution for streaming use cases, often in conjunction with Databricks. Data orchestration Airflow : Airflow is the most common data orchestrator used by data teams.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

DECEMBER 21, 2021

Machine Learning engineers are often required to collaborate with data engineers to build data workflows. As a Google research scientist, one must work on cutting-edge machine intelligence and machine learning systems and generate solutions for real-world, large-scale challenges.

Machine Learning 52

Machine Learning Engineering Algorithm Programming Language 52

Knowledge Hut

MARCH 28, 2024

Strong understanding of cloud computing principles, data warehousing concepts, and best practices. If you’re on the lookout for Azure data engineer job options, you are pacing in the right direction.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

Databand.ai

DECEMBER 29, 2022

In his current role as Senior Director of Product Management at Google, he focuses on BigQuery, Cloud Dataflow, Cloud DataProc, Cloud DataPrep, Cloud PubSub, and Cloud Composer.

Consulting 52

Consulting BI Data Governance Data Science 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 Java Programming Language 52

phData: Data Engineering

JANUARY 3, 2022

This is a config driven tool that is made by HashiCorp and is supported by over 1000+ providers such as: AWS Azure Google Cloud Oracle Alibaba Okta Kubernetes As you can see, there’s support for all the major cloud providers and various other auxiliary tooling that enterprises frequently leverage.

IT 52

IT AWS Software Engineer Software Engineering 52

ProjectPro

JUNE 6, 2025

Airflow enables organizations to orchestrate and automate complex data workflows, making it a crucial tool for building data pipelines in data engineering and data science projects. Learning this powerful tool is a journey that can open doors to efficient data workflows and orchestration.

MySQL 40

MySQL Data Pipeline Metadata Google Cloud 40

AltexSoft

NOVEMBER 7, 2022

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. When Airflow won’t work.

PostgreSQL 52

PostgreSQL Metadata MySQL Python 52