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 113

Data Pipeline Python Data Engineering Data Engineer 113

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Introduction 2. Project demo 3. Use DuckDB 4.4.

Data Pipeline 219

Data Pipeline Python Building Data 219

Confessions of a Data Guy

JULY 24, 2024

We all keep hearing about Arrow this and Arrow that … seems every new tool built today for Data Engineering seems to be at least partly based on Arrow’s in-memory format. So, […] The post PyArrow vs Polars (vs DuckDB) for Data Pipelines. appeared first on Confessions of a Data Guy.

Data Pipeline 162

Data Pipeline Data Engineering Data Engineer Data 162

Confessions of a Data Guy

SEPTEMBER 9, 2023

In the vast world of data, it’s not just about gathering and analyzing information anymore; it’s also about ensuring that data pipelines, processes, and platforms run seamlessly and efficiently.

Data Engineering 162

Data Engineering Data Engineer Engineering Data Pipeline 162

Christophe Blefari

JANUARY 20, 2024

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. Who are the data engineers?

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Analytics Vidhya

NOVEMBER 8, 2023

In the data-driven world […] The post Monitoring Data Quality for Your Big Data Pipelines Made Easy appeared first on Analytics Vidhya. Determine success by the precision of your charts, the equipment’s dependability, and your crew’s expertise. A single mistake, glitch, or slip-up could endanger the trip.

Big Data 246

Big Data Data Pipeline Data IT 246

Databand.ai

JUNE 28, 2023

Data Pipeline Observability: A Model For Data Engineers Eitan Chazbani June 29, 2023 Data pipeline observability is your ability to monitor and understand the state of a data pipeline at any time. We believe the world’s data pipelines need better data observability.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Seattle Data Guy

APRIL 19, 2024

It’s unavoidable that as businesses demand that their data teams implement AI, they will also realize that data engineers are a crucial piece of the data pipeline.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Pipeline 130

KDnuggets

NOVEMBER 25, 2024

Building data pipelines is a very important skill that you should learn as a data engineer. A data pipeline is just a series of procedures that transport data from one location to another, frequently changing it along the way.

Data Pipeline 131

Data Pipeline Building Transportation Data 131

Start Data Engineering

OCTOBER 12, 2021

Introduction Responsibilities of a data engineer 1. Move data between systems 2. Manage data warehouse 3. Schedule, execute, and monitor data pipelines 4. Serve data to the end-users 5. Data strategy for the company 6.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Warehouse 130

Start Data Engineering

MAY 13, 2021

What is an idempotent function Pre-requisites Why idempotency matters Making your data pipeline idempotent Conclusion Further reading References What is an idempotent function “Idempotence is the property of certain operations in mathematics and computer science whereby they can be applied multiple times without changing the result beyond the (..)

Data Pipeline 147

Data Pipeline Computer Science Data Data Engineering 147

Seattle Data Guy

FEBRUARY 11, 2023

Apache Airflow is a very popular tool that data engineers rely on. Why do data engineers like Airflow? What are… Read more The post What Is Apache Airflow – Data Engineering Consulting appeared first on Seattle Data Guy. Also, what does Apache Airflow event do? What is a DAG?

Consulting 147

Consulting Data Engineering Data Engineer Engineering 147

Analytics Vidhya

FEBRUARY 19, 2023

Introduction Data pipelines play a critical role in the processing and management of data in modern organizations. A well-designed data pipeline can help organizations extract valuable insights from their data, automate tedious manual processes, and ensure the accuracy of data processing.

Data Pipeline 197

Data Pipeline Data Designing Data Process 197

Data Engineering Weekly

JUNE 24, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. Bessemer publishes the Data + AI infrastructure market map to help companies understand the landscape and the key players.

Data Engineering 111

Data Engineering Data Engineer Engineering Google Cloud 111

Start Data Engineering

DECEMBER 11, 2022

Data pipeline patterns 3.1. Multi-hop pipelines 3.3.2. Conditional/ Dynamic pipelines 3.3.3. Disconnected data pipelines 4. Source Ordering 2.3. Sink Overwritability 3. Extraction patterns 3.1.1. Time ranged 3.1.2. Full Snapshot 3.1.3. Lookback 3.1.4. Streaming 3.2. Behavioral 3.2.1. Idempotent 3.2.2.

Data Pipeline 195

Data Pipeline Designing Data 195

Start Data Engineering

OCTOBER 11, 2021

Data modeling 4.1 Data warehousing 4.2 Data pipelines 6. Probabilistic data structures (optional) Interview prep, the TL;DR version Conclusion Introduction Are you a student, analyst, engineer, or someone preparing for a data engineering interview and overwhelmed by all the tools and concepts?

Data Engineering 130

Data Engineering Data Engineer Engineering Cloud Computing 130

Data Engineering Weekly

JUNE 10, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. As I have shared , its impact on data engineering is exciting.

Data Engineering 104

Data Engineering Data Engineer Engineering Kafka 104

Data Engineering Podcast

FEBRUARY 18, 2024

In this episode Dain Sundstrom, CTO of Starburst, explains how the combination of the Trino query engine and the Iceberg table format offer the ease of use and execution speed of data warehouses with the infinite storage and scalability of data lakes. Data lakes are notoriously complex. Your first 30 days are free!

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Start Data Engineering

OCTOBER 22, 2021

Data pipeline 2.4. Data analytics 3. Introduction SQL is the bread and butter of data engineering. Narrow transformations 2.2.1.2. Wide transformations 2.2.2. Query planner 2.2.3. Security & Permissions 2.3. Practice 4. Conclusion 5. Further reading 6. References 1.

SQL 130

SQL Data Engineering Data Engineer Engineering 130

Data Engineering Weekly

JUNE 30, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. Engineering jobs saw a 10.42% decline. Learn More → Ozge Demirci, Jonas Hannane & Xinrong Zhu: Who Is AI Replacing?

Data Engineering 103

Data Engineering Data Engineer Engineering Unstructured Data 103

Data Engineering Podcast

MAY 18, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is supported by Code Comments, an original podcast from Red Hat. Data lakes are notoriously complex. My thanks to the team at Code Comments for their support.

Building 278

Building Data Lake High Quality Data Business Intelligence 278

Data Engineering Podcast

JULY 2, 2023

Summary Feature engineering is a crucial aspect of the machine learning workflow. In this episode Razi Raziuddin shares how data engineering teams can support the machine learning workflow through the development and support of systems that empower data scientists and ML engineers to build and maintain their own features.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Engineering 130

Confessions of a Data Guy

JANUARY 13, 2023

Rust has been on my mind a lot lately, probably because of Data Engineering boredom, watching Spark clusters chug along like some medieval farm worker endlessly trudging through the muck and mire of life. appeared first on Confessions of a Data Guy.

Data Pipeline 147

Data Pipeline Data Engineering Data Engineer Data 147

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 106

Data Engineering Data Engineer Engineering Metadata 106

Start Data Engineering

OCTOBER 12, 2021

Introduction Testing your data pipeline 1. Data quality testing 3. Unit and contract testing Conclusion Further reading Introduction Testing data pipelines are different from testing other applications, like a website backend. End-to-end system testing 2. Monitoring and alerting 4.

Data Pipeline 173

Data Pipeline Data Systems 173

Data Engineering Podcast

JUNE 4, 2023

Summary A significant portion of the time spent by data engineering teams is on managing the workflows and operations of their pipelines. Agile Data Engine is a platform designed to handle the infrastructure side of the DataOps equation, as well as providing the insights that you need to manage the human side of the workflow.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Lake 130

Data Engineering Podcast

AUGUST 13, 2023

Summary Data pipelines are the core of every data product, ML model, and business intelligence dashboard. The folks at Rivery distilled the seven principles of modern data pipelines that will help you stay out of trouble and be productive with your data.

Data Pipeline 130

Data Pipeline BI SQL Business Intelligence 130

databricks

JUNE 13, 2024

Today, we are excited to announce Databricks LakeFlow, a new solution that contains everything you need to build and operate production data pipelines.

Data Engineering 144

Data Engineering Data Engineer Engineering Data Pipeline 144

Start Data Engineering

FEBRUARY 22, 2024

Data Pipeline Logging Best Practices 3.1. Metadata: Information about pipeline runs, & data flowing through your pipeline 3.2. Introduction 2. Setup & Logging architecture 3. Obtain visibility into the code’s execution sequence using text logs 3.3. Understand resource usage by tracking Metrics 3.4.

Metadata 130

Metadata Data Engineering Data Engineer Engineering 130

Data Engineering Podcast

APRIL 14, 2024

The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database.

Non-relational Database 147

Non-relational Database Relational Database Database Designing 147

Netflix Tech

DECEMBER 3, 2022

by Jasmine Omeke , Obi-Ike Nwoke , Olek Gorajek Intro This post is for all data practitioners, who are interested in learning about bootstrapping, standardization and automation of batch data pipelines at Netflix. You may remember Dataflow from the post we wrote last year titled Data pipeline asset management with Dataflow.

Data Pipeline 144

Data Pipeline Scala Metadata Food 144

Data Engineering Weekly

JUNE 16, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. Unity Catalog's source code is available on GitHub, and people have already conducted exciting experiments with it.

Data Engineering 105

Data Engineering Data Engineer Engineering Kafka 105

Start Data Engineering

DECEMBER 12, 2021

Introduction If you are building data pipelines from the ground up, the number of available data engineering tools to choose from can be overwhelming. Components 4. Choosing tools 4.1 Requirement x Component framework 4.2 Conclusion 6. Further reading 1.

Data Pipeline 130

Data Pipeline Data Engineering Data Engineer Data 130

Data Engineering Podcast

MAY 22, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Analytics Vidhya

SEPTEMBER 12, 2024

Introduction Imagine yourself as a data professional tasked with creating an efficient data pipeline to streamline processes and generate real-time information. Sounds challenging, right? That’s where Mage AI comes in to ensure that the lenders operating online gain a competitive edge.

Data Pipeline 144

Data Pipeline Building Management Data 144

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions.

Data Engineering 109

Data Engineering Data Engineer Engineering Metadata 109

Data Engineering Podcast

JUNE 30, 2024

Petr shares his journey from being an engineer to founding Synq, emphasizing the importance of treating data systems with the same rigor as engineering systems. He discusses the challenges and solutions in data reliability, including the need for transparency and ownership in data systems.

Pipeline-centric 147

Pipeline-centric Engineering Data Lake High Quality Data 147