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.

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Data Engineering Data Engineer Engineering Google Cloud 109

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. link] Picnic: Open-sourcing dbt-score: lint model metadata with ease!

Data Engineering 104

Data Engineering Data Engineer Engineering Kafka 104

Data Engineering Podcast

NOVEMBER 10, 2021

Summary A significant source of friction and wasted effort in building and integrating data management systems is the fragmentation of metadata across various tools. 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!

Metadata 100

Metadata Data Warehouse Data Lake BI 100

Snowflake

JANUARY 25, 2023

Over the multiple decades I’ve spent in the data industry, one observation has remained nearly constant: the majority of the work in building a data analytics platform revolves around data transformations (what we used to call “the T in ETL or ELT”). We cannot scale our expertise as fast as we can scale the Data Cloud.

Metadata 82

Metadata Data Pipeline Government Data 82

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 107

Data Engineering Data Engineer Engineering Metadata 107

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

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.

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Data Pipeline Datasets Metadata Data 52

Data Engineering Weekly

NOVEMBER 3, 2024

The blog emphasizes the importance of starting with a clear client focus to avoid over-engineering and ensure user-centric development. Sampling is an obvious strategy for data size, but the layered approach and dynamic inclusion of dependencies are some key techniques I learned with the case study.

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Data Engineering Data Engineer Engineering Pipeline-centric 62

Data Science Blog: Data Engineering

MAY 20, 2024

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. They transform data into a consistent format for users to consume.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Data Engineering Podcast

OCTOBER 15, 2021

Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. How is the governance of DataHub being managed?

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Metadata BI Data Warehouse Government 100

Data Engineering Weekly

AUGUST 25, 2024

Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. Try For Free → Conference Alert: Data Engineering for AI/ML This is a virtual conference at the intersection of Data and AI.

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Data Engineering Data Engineer Engineering Database-centric 70

Data Engineering Weekly

SEPTEMBER 22, 2024

Uber: QueryGPT – Natural Language to SQL Using Generative AI Companies are increasingly adopting the natural language interface to interact with the enterprise data. Dropbox writes a case study on integrating Lakera Guard into their prompt engineering to secure the LLM infrastructure.

Data Engineering 70

Data Engineering Data Engineer Engineering Data Lake 70

Christophe Blefari

MARCH 15, 2024

Cognition AI introduced Devin — Devin is the first AI software engineer, Devin can, unassisted, do software engineering tasks like fixing Github issues (13% of success, previously best was ~5%), apply to jobs on Upwork, train and fine-tune its own models. Arrow doing a lot of the data operation heavy lifting.

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Metadata Datasets Data Data Warehouse 272

Data Engineering Weekly

SEPTEMBER 15, 2024

Whether or not Data Mesh is a separate product is debatable, but it is certainly an impactful framework for scaling data platforms. link] Miro: Data Products Reliability - The Power of Metadata Miro writes about its adoption of Data Contracts.

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Data Engineering Data Engineer Engineering Data Lake 67

Data Engineering Podcast

JUNE 16, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Powered by Trino, the query engine Apache Iceberg was designed for, Starburst is an open platform with support for all table formats including Apache Iceberg, Hive, and Delta Lake.

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Data Lake High Quality Data Metadata Machine Learning 147

Data Engineering Weekly

OCTOBER 6, 2024

The learning goes back to the fundamentals of pipeline design principles. Regularly review if pipelines are still required. Minimize the data used in pipelines, aka do incremental data pipeline design. Optimize pipeline schedules. Filter data effectively to make sure the query uses partition pruning.

Data Engineering 62

Data Engineering Data Engineer Engineering Data Warehouse 62

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

Ascend.io

SEPTEMBER 25, 2023

European data teams can now build and automate data pipelines with the ease of a managed SaaS offering while meeting stringent data sovereignty requirements. As Ascend’s partners Snowflake and Databricks continue to expand in the region, the demand for scalable data pipeline solutions has skyrocketed.

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Data Pipeline Data Architect Metadata Media 52

Data Engineering Weekly

JULY 7, 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. The author highlights Paimon’s consistency model by examining the metadata model.

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Data Engineering Data Engineer Engineering Data Lake 98

Data Engineering Weekly

AUGUST 18, 2024

Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. The content search engine has two layers: a retrieval layer and a multi-stage ranking layer. Hudi maintains the current snapshot in the metadata table.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

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. Data orchestration refers to a wide collection of methods and tools that coordinate any and all types of data-related computing tasks.

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Data Pipeline IT Data Data Engineering 52

Workfall

AUGUST 14, 2023

Reading Time: 7 minutes In today’s data-driven world, efficient data pipelines have become the backbone of successful organizations. These pipelines ensure that data flows smoothly from various sources to its intended destinations, enabling businesses to make informed decisions and gain valuable insights.

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Data Pipeline Data Raw Data Database 62

Ascend.io

MAY 8, 2023

The costs of developing and running data pipelines are coming under increasing scrutiny because the bills for infrastructure and data engineering talent are piling up. For data teams, it is time to ask: “How can we have an impact on these runaway costs and still deliver unprecedented business value?”

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Data Pipeline Data Ingestion Metadata Data 52

Data Engineering Podcast

AUGUST 13, 2022

In this episode Shinji Kim discusses the challenges of data discovery and how to collect and preserve additional context about each piece of information so that you can find what you need when you don’t even know what you’re looking for yet. Data stacks are becoming more and more complex.

Metadata 100

Metadata MongoDB Scala MySQL 100

Cloudera

FEBRUARY 8, 2021

Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. 1): Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a vehicle showroom). Conclusion.

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Data Pipeline Building Manufacturing Data Warehouse 118

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. You can observe your pipelines with built in metadata search and column level lineage.

Data Engineering 100

Data Engineering Data Engineer Engineering Python 100

Ascend.io

FEBRUARY 2, 2023

2, 2023 — Ascend.io, the leader in Data Pipeline Automation for building the world’s most intelligent data pipelines, is expanding its global presence and has hired Robin Rostratter as Head of EMEA sales to better engage and support the company’s customer base across Europe. . SAN FRANCISCO , Feb.

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Data Pipeline Google Cloud Metadata Media 52

Ascend.io

FEBRUARY 2, 2023

2, 2023 — Ascend.io, the leader in Data Pipeline Automation for building the world’s most intelligent data pipelines, is expanding its global presence and has hired Robin Rostratter as Head of EMEA sales to better engage and support the company’s customer base across Europe. . SAN FRANCISCO , Feb.

Data Pipeline 52

Data Pipeline Google Cloud Metadata Media 52

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.

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Machine Learning Data Engineering Data Engineer Cloud 130

Data Engineering Podcast

AUGUST 28, 2022

Summary The dream of every engineer is to automate all of their tasks. For data engineers, this is a monumental undertaking. Orchestration engines are one step in that direction, but they are not a complete solution. Atlan is the metadata hub for your data ecosystem.

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Data Engineering Data Engineer MongoDB Metadata 100

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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Data Engineering Data Engineer Engineering Metadata 52

Data Engineering Podcast

NOVEMBER 20, 2022

Summary The majority of blog posts and presentations about data engineering and analytics assume that the consumers of those efforts are internal business users accessing an environment controlled by the business. Atlan is the metadata hub for your data ecosystem.

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Systems Metadata Data Pipeline MongoDB 130

Ascend.io

JULY 23, 2024

Data engineering is evolving rapidly, driven by advancements in AI and automation. This article (based on the webinar below) explores how data engineering teams can leverage AI and automation to enhance productivity and tackle current challenges. This sobering statistic has haunted well-intentioned data teams for years.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Data Engineering Podcast

JANUARY 15, 2022

In this episode Brian McMillan shares his work on the book "Building Data Products" and how he is working to educate business users and data professionals about the combination of technical, economical, and business considerations that need to be blended for these projects to succeed.

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Engineering Electronics Data Pipeline ETL Tools 100

Towards Data Science

OCTOBER 25, 2023

Not too long ago, almost all data architectures and data team structures followed a centralized approach. As a data or analytics engineer, you knew where to find all the transformation logic and models because they were all in the same codebase. There was only one data team, two at most. How did they do it?

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Data Pipeline SQL Data Architecture Data 78

Data Engineering Podcast

DECEMBER 18, 2022

In this episode Abe Gong brings his experiences with the Great Expectations project and community to discuss the technical and organizational considerations involved in implementing these constraints to your data workflows. Atlan is the metadata hub for your data ecosystem. Struggling with broken pipelines? Missing data?

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Metadata Business Intelligence Data Lake BI 130