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.

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Data Pipeline Python Datasets Database 130

Start Data Engineering

JANUARY 12, 2023

Singleton, & Object pool patterns Python helpers 1. Introduction Sample project Code design patterns 1. Functional design 2. Factory pattern 3. Strategy pattern 4. Dataclass 3. Context Managers 4. Testing with pytest 5.

Designing 147

Designing Coding Python Data Pipeline 147

Data Engineering Weekly

MAY 26, 2024

link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. seconds, enhancing real-time sports data analytics efficiency! The author highlights some of the key missing features from S3.

Data Engineering 57

Data Engineering Data Engineer Engineering Google Cloud 57

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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Data Engineering Data Engineer Python Engineering 52

Towards Data Science

NOVEMBER 4, 2023

Platform Specific Tools and Advanced Techniques Photo by Christopher Burns on Unsplash The modern data ecosystem keeps evolving and new data tools emerge now and then. In this article, I want to talk about crucial things that affect data engineers. Are your data pipelines efficient? Data warehouse exmaple.

Data Engineering 83

Data Engineering Data Engineer Engineering BI 83

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

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

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.

Data Pipeline 130

Data Pipeline Building MongoDB Scala 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

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? What is Data Science?

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Data Engineering Data Engineer Engineering Pipeline-centric 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

Snowflake

AUGUST 24, 2023

The family of companies, a part of Radian Group, relies on data science and machine learning to build and deploy models using a variety of data from different sources to bring technology to all parts of the home-buyer experience. This became a bottle neck for a growing advanced analytics team developing cutting edge technologies.

Data Pipeline 52

Data Pipeline Python Programming Language Data Validation 52

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 discusses the significance of data governance, sharing history, and generative AI's impact on data economy standards.

Data Engineering 70

Data Engineering Data Engineer Engineering Data Governance 70

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance. Enterprise Data Engineering From the Ground Up.

Data Pipeline 103

Data Pipeline Data Engineering Data Engineer Engineering 103

Data Engineering Podcast

MAY 12, 2024

Summary Building a data platform is a substrantial engineering endeavor. 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.

Management 147

Management Data Lake High Quality Data Machine Learning 147

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

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.

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Data Pipeline Scala Metadata Food 143

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 126

Data Engineering Data Engineer Engineering Pipeline-centric 126

Data Engineering Podcast

MAY 26, 2024

When that system is responsible for the data layer the process becomes more challenging. Sriram Panyam has been involved in several projects that required migration of large volumes of data in high traffic environments. Can you start by sharing some of your experiences with data migration projects?

Systems 130

Systems Data Lake High Quality Data Google Cloud 130

Data Engineering Weekly

MARCH 31, 2024

Intuit: How Intuit data analysts write SQL 2x faster with the internal GenAI tool The productivity increase with GenAI is undeniable, and several startups are trying to solve the Text2SQL generation problem. My key highlight is that Excellent data documentation and “clean data” improve results.

Data Engineering 62

Data Engineering Data Engineer Engineering Scala 62

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.

Data Engineering 100

Data Engineering Data Engineer Engineering Data Pipeline 100

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.

Data Engineering 81

Data Engineering Data Engineer Engineering SQL 81

Towards Data Science

MARCH 9, 2024

A gentle introduction to unit testing, mocking and patching for beginners Continue reading on Towards Data Science »

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Data Pipeline Python Data Science Data 73

Data Engineering Podcast

MARCH 24, 2024

Summary A core differentiator of Dagster in the ecosystem of data orchestration is their focus on software defined assets as a means of building declarative workflows. Data lakes are notoriously complex. Your first 30 days are free! Want to see Starburst in action? Can you describe what the focus of Dagster+ is and the story behind it?

Data Lake 162

Data Lake High Quality Data Hadoop Data Pipeline 162

Data Engineering Podcast

APRIL 7, 2024

Summary Maintaining a single source of truth for your data is the biggest challenge in data engineering. Different roles and tasks in the business need their own ways to access and analyze the data in the organization. Dagster offers a new approach to building and running data platforms and data pipelines.

Data Lake 162

Data Lake High Quality Data BI Data Workflow 162

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

KDnuggets

SEPTEMBER 5, 2023

Build a streaming data pipeline using Formula 1 data, Python, Kafka, RisingWave as the streaming database, and visualize all the real-time data in Grafana.

Data Pipeline 98

Data Pipeline Kafka Building Python 98

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?

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

MAY 3, 2023

Did you know that data is now an essential component of modern business operations? With companies increasingly relying on data-driven insights to make informed decisions, there has never been a greater need for skilled specialists who can manage and evaluate vast amounts of data.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Cleanse 98

Towards Data Science

DECEMBER 4, 2023

A Glossary with Use Cases for First-Timers in Data Engineering An happy Data Engineer at work Are you a data engineering rookie interested in knowing more about modern data infrastructures? In this guide Data Engineering meets Formula 1. I bet you are, this article is for you!

Data Engineering 84

Data Engineering Data Engineer Engineering Data Lake 84

Data Engineering Podcast

FEBRUARY 4, 2024

In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

Data Engineering Podcast

APRIL 23, 2023

Meroxa was created to enable teams of all sizes to deliver real-time data applications. In this episode DeVaris Brown discusses the types of applications that are possible when teams don't have to manage the complex infrastructure necessary to support continuous data flows. Can you describe what Meroxa is and the story behind it?

Data Lake 277

Data Lake Kafka Machine Learning Data Warehouse 277

Data Engineering Podcast

FEBRUARY 11, 2024

Summary Sharing data is a simple concept, but complicated to implement well. There are also numerous technical considerations to be made, particularly if the producer and consumer of the data aren't using the same platforms. Dagster offers a new approach to building and running data platforms and data pipelines.

Data Lake 147

Data Lake High Quality Data Government Data Pipeline 147

Data Engineering Podcast

APRIL 21, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Data lakes are notoriously complex. Your first 30 days are free! Want to see Starburst in action?

Data Lake 182

Data Lake High Quality Data Data Pipeline Machine Learning 182

Christophe Blefari

MARCH 2, 2024

Mistral ( credits ) Hello all, this is the Data News, this week edition might be smaller than usual in term of comments as I'm working on a Data News related project that takes me a bit of time, which will probably lead to a series of articles. In 2024 we are more than ever tools to move data from sources to destinations.

Data 162

Data Python Database BI 162

Data Engineering Podcast

MARCH 17, 2024

Summary A significant portion of data workflows involve storing and processing information in database engines. In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Data lakes are notoriously complex.

Database 147

Database Data Lake High Quality Data Data Workflow 147

Team Data Science

MAY 10, 2020

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. I'll use Python and Spark because they are the top 2 requested skills in Toronto. With careful consideration and learning about your market, the choices you need to make become narrower and more clear.

Data Pipeline 130

Data Pipeline Data Ingestion AWS Kafka 130