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! In this video, Sr.

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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.

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Analytics Vidhya

FEBRUARY 6, 2023

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary. appeared first on Analytics Vidhya.

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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. How is this distinct from other forms of data pipeline development and delivery?

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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?

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Data Engineering Weekly

MARCH 17, 2024

Compliance is mandatory, with strict penalties for violations, emphasizing the importance of data scientists familiarizing themselves with the law to avoid prohibited AI uses and ensure ethical, safe AI development. It also introduces emerging standards like the Open Data Contract Standard and Data Product Descriptor Specification.

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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.

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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.

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RandomTrees

FEBRUARY 2, 2024

GPT-based data engineering accelerators make the working of data more accessible. These accelerators use GPT models to do data tasks faster, fix any issues, and save a lot of time. GPT models change data in simple language and also provide summaries and explanations. One can rely on this information.

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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.

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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.

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Data Engineering Weekly

MARCH 3, 2024

Editor’s Note: Chennai, India Meetup - March-08 Update We are thankful to Ideas2IT to host our first Data Hero’s meetup. There will be food, networking, and real-world talks around data engineering. link] Martin Chesbrough: How to Build a Modern Data Team?

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Towards Data Science

AUGUST 19, 2023

How I made the transition to an analytics engineer Photo by Campaign Creators on Unsplash A few years ago, I was at a point where I was feeling unfulfilled in my career. I had been working in data engineering for three years and the initial excitement of starting in the world of tech had faded.

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Data Engineering Weekly

DECEMBER 3, 2023

link] Microsoft: Generative AI for Beginners Understanding Gen-AI becomes a mandatory skill for application developers and data engineers. Netflix writes about its membership data pipeline and how it supports the lookback approach. We plan to leverage multiple new use cases in ClickHouse.

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Knowledge Hut

MARCH 15, 2024

At the same time, it has opened up a wealth of opportunities for data engineers. With businesses harnessing the power of Azure’s services, the need for skilled data engineers has topped the charts. Speaking from experience, the data engineers in this role are right in the thick of it all.

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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. . Prerequisites for deploying CDP Data Engineering on Azure can be found here.

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Knowledge Hut

MARCH 20, 2024

At the same time, it has opened up a wealth of opportunities for data engineers. With businesses harnessing the power of Azure’s services, the need for skilled data engineers has topped the charts. Speaking from experience, the data engineers in this role are right in the thick of it all.

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Data Engineering Weekly

MARCH 10, 2024

link] Yelp: Building data abstractions with streaming at Yelp Yelp has revamped its data pipeline to stream huge volumes of data in real time, focusing on building robust data abstractions for offline and streaming data consumers. Data engineers build the systems that store and process sensitive information.

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Towards Data Science

FEBRUARY 24, 2023

The Chaos Data-Engineering Manifesto Another lesson we can learn from software engineers: break stuff to make it more reliable. While this idea isn’t completely foreign to data engineering, it can certainly be described as an extremely uncommon practice. Data is different. It’s terrifying. I’m afraid so.

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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?

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Data Engineering Weekly

OCTOBER 1, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. What is the data behavior? See how it works today. Dropbox: Is this a date?

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Data Engineering Podcast

JANUARY 30, 2022

Summary Pandas is a powerful tool for cleaning, transforming, manipulating, or enriching data, among many other potential uses. As a result it has become a standard tool for data engineers for a wide range of applications. The only thing worse than having bad data is not knowing that you have it.

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Knowledge Hut

JUNE 26, 2023

Welcome to the world of data engineering, where the power of big data unfolds. If you're aspiring to be a data engineer and seeking to showcase your skills or gain hands-on experience, you've landed in the right spot. What are Data Engineering Projects?

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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.

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Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

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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?

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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.

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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.

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Towards Data Science

MARCH 23, 2024

Data pipelines that would turn you into a decorated data professional Continue reading on Towards Data Science »

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Towards Data Science

AUGUST 22, 2023

As a founder of a VC funded startup in the data / technology space, I’ve seen a lot of things and have spoken to a lot of other founders. A lot of readers are probably familiar with working at a “big company” as a data engineer. You want to understand how critical the data pipelines are for the business.

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Knowledge Hut

MARCH 28, 2024

Data engineering is one of them. According to AnalytixLabs , the data science market is expected to be worth USD 230.80 All these numbers point to one thing–increased job roles and careers, especially when we talk about data engineering jobs in Azure, which are on the rise every year. Let’s get started.

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Ascend.io

SEPTEMBER 14, 2023

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

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KDnuggets

MARCH 17, 2020

As the role of the data engineer continues to grow in the field of data science, so are the many tools being developed to support wrangling all that data. Five of these tools are reviewed here (along with a few bonus tools) that you should pay attention to for your data pipeline work.

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Monte Carlo

FEBRUARY 27, 2024

If you’re a data engineer experiencing GenAI-induced whiplash, you’re not alone. On one hand, everyone’s talking about whether GenAI’s not-insignificant data engineering skills are going to automate away their jobs. They need robust data pipelines, high-quality data, well-guarded privacy, and cost-effective scalability.

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Towards Data Science

DECEMBER 11, 2023

Streaming data pipelines and real-time analytics Continue reading on Towards Data Science »

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Data Engineering Weekly

MARCH 19, 2023

The article discusses incremental processing strategy, handling late-arriving data, and backfilling with the design patterns explaining how Apache Hudi simplifies ETL processing. link] Data Engineering Weekly talks in detail about adopting functional data engineering principles, and Apache Hudi certainly supports it out of the box.

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Knowledge Hut

MARCH 13, 2024

Wondering what is a big data engineer? As the name suggests, Big Data is associated with ‘big’ data, which hints at something big in the context of data. Big data forms one of the pillars of data science. Big data has been a hot topic in the IT sector for quite a long time.

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