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

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 Podcast

JUNE 25, 2023

Summary Data transformation is a key activity for all of the organizational roles that interact with data. Because of its importance and outsized impact on what is possible for downstream data consumers it is critical that everyone is able to collaborate seamlessly. Can you describe what SQLMesh is and the story behind it?

Data Engineering 225

Data Engineering Data Engineer Python Engineering 225

Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

Data Engineering 189

Data Engineering Data Engineer Engineering Project 189

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

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

Snowflake

APRIL 17, 2024

In today’s data-driven world, developer productivity is essential for organizations to build effective and reliable products, accelerate time to value, and fuel ongoing innovation. This allows your applications to handle large data sets and complex workflows efficiently.

Data Pipeline 112

Data Pipeline Python Data Engineering Data Engineer 112

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. appeared first on Confessions of a Data Guy.

Data Pipeline 147

Data Pipeline Data Engineering Data Engineer Data 147

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

Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Join in with the event for the global data community, Data Council Austin.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

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

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 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 Machine Learning 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

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

Cloudera

JULY 13, 2021

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . CDP data lifecycle integration and SDX security and governance. Easy job deployment.

Data Engineering 128

Data Engineering Data Engineer Engineering Pipeline-centric 128

Seattle Data Guy

APRIL 19, 2024

How data is structured, managed and processed will continue to grow in importance as the demand for AI and machine learning increase. 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

Start Data Engineering

SEPTEMBER 16, 2021

Introduction Choosing tools/frameworks to scale your data pipelines can be confusing. If you have struggled with Data pipelines that randomly crash Finding guides on how to scale your data pipelines from the ground up Then this post is for you. Choose your scaling strategy 5. Conclusion 6. Further reading 7.

Data Pipeline 130

Data Pipeline Data IT 130

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

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

SEPTEMBER 11, 2022

Summary Any business that wants to understand their operations and customers through data requires some form of pipeline. Building reliable data pipelines is a complex and costly undertaking with many layered requirements. Data stacks are becoming more and more complex. Sifflet also offers a 2-week free trial.

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Data Pipeline Building MongoDB MySQL 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 106

Data Pipeline Building Transportation Data 106

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

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. A few highlights from the report Unstructured data goes mainstream. AI-driven code development is going mainstream now.

Data Engineering 109

Data Engineering Data Engineer Engineering Google Cloud 109

Start Data Engineering

OCTOBER 11, 2021

Leetcode: data structures and algorithms 4. Data modeling 4.1 Data warehousing 4.2 Data pipelines 6. Introduction Skills 1. Distributed system fundamentals 7. Event streaming 8. System design 9. Business questions 10. Cloud computing 11.

Data Engineering 130

Data Engineering Data Engineer Engineering Cloud Computing 130

Data Engineering Podcast

MAY 18, 2024

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Data lakes are notoriously complex.

Building 278

Building Data Lake High Quality Data Business Intelligence 278

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. Databricks and Snowflake offer a data warehouse on top of cloud providers like AWS, Google Cloud, and Azure.

Data Engineering 103

Data Engineering Data Engineer Engineering Kafka 103

Start Data Engineering

OCTOBER 22, 2021

Data modeling 2.1.1. Data storage 2.2. Data transformation 2.2.1. Data pipeline 2.4. Data analytics 3. Introduction SQL is the bread and butter of data engineering. Introduction 2. SQL skills 2.1. Gathering requirements 2.1.2. Exploration 2.1.3. Modeling 2.1.4. Transformation types 2.2.1.1.

SQL 130

SQL Data Engineering Data Engineer Engineering 130

Start Data Engineering

NOVEMBER 11, 2021

Writing an end-to-end data pipeline test 4. Introduction Data pipelines can have multiple software components. If you are wondering What is the best way to end-to-end test data pipelines? In this post, we go over some techniques that you can use to set up end-to-end tests for your data pipelines.

Data Pipeline 130

Data Pipeline Cloud Data 130

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

Confessions of a Data Guy

MARCH 29, 2024

Have you ever wondered at a high level what it’s like to build production-level data pipelines on Databricks? The post Building Databricks Data Pipelines 101 appeared first on Confessions of a Data Guy. What does it look like, what tools do you use?

Data Pipeline 100

Data Pipeline Building Data IT 100

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. Looming regulatory requirements, data quality, governance issues & model accuracy keep failing enterprises.

Data Engineering 102

Data Engineering Data Engineer Engineering Unstructured Data 102

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 140

Data Engineering Data Engineer Engineering Data Pipeline 140

Data Engineering Podcast

JULY 2, 2023

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. What is feature engineering is and why/to whom it matters?

Machine Learning 130

Machine Learning Data Engineering Data Engineer Engineering 130

Simon Späti

JUNE 20, 2022

Data consumers, such as data analysts, and business users, care mostly about the production of data assets. On the other hand, data engineers have historically focused on modeling the dependencies between tasks (instead of data assets) with an orchestrator tool. How can we reconcile both worlds?

Data Pipeline 147

Data Pipeline Data Data Engineering Data Engineer 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

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