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

Start Data Engineering

APRIL 8, 2021

Understand the current state of the data pipeline 1. Timelines & deliverables Deliver iteratively Conclusion Further reading References Introduction As data engineers, you will have to re-engineer legacy data pipelines. While re-engineering data pipelines, if you have struggled with

Data Pipeline 130

Data Pipeline Engineering Data Data Engineering 130

Analytics Vidhya

JUNE 25, 2023

In a data-driven world, behind-the-scenes heroes like data engineers play a crucial role in ensuring smooth data flow. A data engineer investigates the issue, identifies a glitch in the e-commerce platform’s data funnel, and swiftly implements seamless data pipelines.

Data Engineering 220

Data Engineering Data Engineer Engineering Data Pipeline 220

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

LinkedIn Engineering

JUNE 26, 2023

However, we've found that this vertical self-service model doesn't work particularly well for data pipelines, which involve wiring together many different systems into end-to-end data flows. Data pipelines power foundational parts of LinkedIn's infrastructure, including replication between data centers.

Data Pipeline 112

Data Pipeline Kafka MySQL SQL 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.

Data Pipeline 147

Data Pipeline Data Engineering Data Engineer Data 147

Analytics Vidhya

APRIL 3, 2023

Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers. Nevertheless, setting up a streaming data pipeline to power such dashboards may […] The post Data Engineering for Streaming Data on GCP appeared first on Analytics Vidhya.

Data Engineering 251

Data Engineering Data Engineer Engineering Data 251

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

Precisely

DECEMBER 28, 2023

Business success is based on how we use continuously changing data. That’s where streaming data pipelines come into play. This article explores what streaming data pipelines are, how they work, and how to build this data pipeline architecture. What is a streaming data pipeline?

Data Pipeline 91

Data Pipeline Building Kafka Big Data 91

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

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

Picnic Engineering

FEBRUARY 8, 2023

In our previous blog, Dima Kalashnikov explained how we configure our Internal services pipeline in the Analytics Platform. In this post, we will explain how our team automates the creation of new data pipeline deployments. Now, we can have a pipeline ready in minutes.

Data Pipeline 105

Data Pipeline Kafka Data Architecture 105

Towards Data Science

APRIL 3, 2023

Data pipeline management done right simplifies deployment and increases the availability and accessibility of data for analytics Continue reading on Towards Data Science »

Data Pipeline 81

Data Pipeline Data Science Data Accessible 81

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

Data Engineering Podcast

SEPTEMBER 11, 2022

Building reliable data pipelines is a complex and costly undertaking with many layered requirements. In order to reduce the amount of time and effort required to build pipelines that power critical insights Manish Jethani co-founded Hevo Data. Data stacks are becoming more and more complex.

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Towards Data Science

MARCH 3, 2024

Data engineering techniques for robust and sustainable ETL Continue reading on Towards Data Science »

Data Pipeline 79

Data Pipeline Building Data Science Data 79

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

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 Data Engineering Data Engineer 130

Snowflake

OCTOBER 3, 2023

We are excited to announce the availability of data pipelines replication, which is now in public preview. In the event of an outage, this powerful new capability lets you easily replicate and failover your entire data ingestion and transformations pipelines in Snowflake with minimal downtime.

Data Pipeline 76

Data Pipeline Management Data Ingestion Data 76

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 103

Data Engineering Data Engineer Engineering Metadata 103

Ascend.io

APRIL 26, 2023

Data teams worldwide are building data pipelines with the point solutions that make up the “modern data stack.” Pipelines built with this approach are slow and require constant manual reprogramming and updates. For a deep dive into this level of automation, take a look at our What Is Data Pipeline Automation paper.

Data Pipeline 52

Data Pipeline Datasets Metadata Data 52

Monte Carlo

FEBRUARY 8, 2024

Just as a watchmaker meticulously adjusts every tiny gear and spring in harmonious synchrony for flawless performance, modern data pipeline optimization requires a similar level of finesse and attention to detail. Learn how cost, processing speed, resilience, and data quality all contribute to effective data pipeline optimization.

Data Pipeline 52

Data Pipeline AWS Datasets Data 52

Ascend.io

JANUARY 2, 2024

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

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

OCTOBER 28, 2021

In this episode Eric Sammer discusses the shortcomings of the current set of streaming engines and how they force engineers to work at an extremely low level of abstraction. Data engineers struggling with unreliable data need look no further than Monte Carlo, the world’s first end-to-end, fully automated Data Observability Platform!

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Data Pipeline SQL Data Warehouse Data Lake 100

Ascend.io

MARCH 17, 2023

As a result, stakeholders limit their reliance on data, making decisions based on gut instinct rather than facts. To shift this harmful approach, companies need to make fundamental changes to their data engineering function and start running at speed and with agility. In fact, it’s been a recurring theme in software engineering.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

As a result, stakeholders limit their reliance on data, making decisions based on gut instinct rather than facts. To shift this harmful approach, companies need to make fundamental changes to their data engineering function and start running at speed and with agility. In fact, it’s been a recurring theme in software engineering.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Towards Data Science

SEPTEMBER 10, 2023

Realities of company and cloud complexities require new levels of control and autonomy to meet business goals at scale Image by Cosmin Paduraru As data teams scale up on the cloud, data platform teams need to ensure the workloads they are responsible for are meeting business objectives. Sounds like a dream.

Data Pipeline 91

Data Pipeline Data Utilities Coding 91

Data Engineering Podcast

JUNE 25, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform.

Data Engineering 225

Data Engineering Data Engineer Python Engineering 225

Confluent

SEPTEMBER 26, 2023

Confluent's Q3 '23 Launch brings intelligent, secure, cost-effective data pipelines with cloud-native Apache Flink, enterprise clusters powered by Kora engine, and more.

Data Pipeline 70

Data Pipeline Data Cloud Engineering 70

Data Engineering Podcast

NOVEMBER 12, 2023

Generative AI has accelerated the ability of developer tools to provide useful suggestions that speed up the work of engineers. Tabnine is one of the main platforms offering an AI powered assistant for software engineers. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold Data lakes are notoriously complex.

Software Engineer 147

Software Engineer Software Engineering Engineering Data Lake 147

Ascend.io

AUGUST 22, 2023

The demands of building, scaling, and maintaining data pipelines have grown increasingly complex and error-prone. Data engineers are now drowning in repetitive tasks, aspiring to drive data-backed decisions. Traditional approaches to building these pipelines have showcased their vulnerabilities.

Data Pipeline 52

Data Pipeline Raw Data Bytes Transportation 52

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

Monte Carlo

JANUARY 23, 2024

In the world of data engineering, Maxime Beauchemin is someone who needs no introduction. Currently, Maxime is CEO and co-founder of Preset , a fast-growing startup that’s paving the way forward for AI-enabled data visualization for modern companies. Enter, the data engineer. What is a data engineer today?

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Data Engineering Data Engineer Engineering Data 98

Towards Data Science

NOVEMBER 4, 2023

In this article, I want to talk about crucial things that affect data engineers. We will discuss how to use this knowledge to power advanced analytics pipelines and operational excellence. I’d like to discuss some popular Data engineering questions: Modern data engineering (DE). What is it?

Data Engineering 88

Data Engineering Data Engineer Engineering BI 88

Start Data Engineering

APRIL 26, 2021

Using distributed frameworks Pros & Cons Conclusion Further reading References Introduction If you are Wondering how to write memory efficient data pipelines in python Working with a dataset that is too large to fit into memory Then this post is for you.

Data Pipeline 130

Data Pipeline Python Datasets Database 130

Ascend.io

NOVEMBER 28, 2023

The terms ‘data orchestration’ and ‘data pipeline orchestration’ are often used interchangeably, yet they diverge significantly in function and scope. In contrast, data pipeline orchestration is a more targeted approach. What Is Data Pipeline Orchestration?

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Data Pipeline IT Data Metadata 52