Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

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Metadata MongoDB Scala MySQL 130

Data Engineering Weekly

DECEMBER 18, 2023

Lorin Hochstein: “Human error” means they don’t understand how the system worked The post is not directly related to Data Engineering but system operations in general. It is great to see an internal tech talk with a series focus on data engineering. Visit rudderstack.com to learn more.

Data Engineering 67

Data Engineering Data Engineer Engineering Food 67

Data Engineering Weekly

MARCH 10, 2024

Pradheep Arjunan - Shared insights on AZ's journey from on-prem to the cloud data warehouses. Google: Croissant- a metadata format for ML-ready datasets Google Research introduced Croissant, a new metadata format designed to make datasets ML-ready by standardizing the format, facilitating easier use in machine learning projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

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?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

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.

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Data Pipeline BI Data Lake Data Warehouse 52

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 Data Pipeline 100

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

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.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Towards Data Science

APRIL 3, 2023

If you don’t like change, data engineering is not for you. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

RandomTrees

FEBRUARY 6, 2024

Data engineering, the practice of collecting, transforming, and organizing data for analysis, is poised for a significant transformation with the advent of Generative Artificial Intelligence (Gen AI). Generative AI with ETL Pipelines: Generative AI can be used to automate the creation of ETL pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

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

Data Engineering Weekly

JULY 2, 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. So, let's shape the future of Data Engineering together.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

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.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 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

Data Engineering Weekly

OCTOBER 23, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Hello Data Friends, Welcome to another edition of Data Engineering Weekly.

Data Engineering 52

Data Engineering Data Engineer Engineering Deep Learning 52

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. Data Engineer certification will aid in scaling up you knowledge and learning of data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

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

Data Engineering Weekly

DECEMBER 4, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. link] Barr Moses: What’s Next for Data Engineering in 2023?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Ascend.io

AUGUST 16, 2023

August 16, 2023 — Ascend.io , the leader in data pipeline automation, today released an economic analysis report conducted by Enterprise Strategy Group (ESG) of its Data Pipeline Automation Platform. As enterprise usage of data analytics grows, the field has become a significant area of IT expenditure.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Data Engineering Weekly

OCTOBER 30, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. Sign up free to test out the tool today.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 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?

Metadata 100

Metadata BI Data Warehouse Government 100

Data Engineering Weekly

JANUARY 15, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. 2023 predictions from the panel are; Unified metadata becomes kingmaker.

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Data Engineering Data Engineer Engineering Metadata 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

Grouparoo

OCTOBER 6, 2021

It was a fun experience and I think we made a good choice by picking 97 Things Every Data Engineer Should Know. This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

AltexSoft

OCTOBER 30, 2021

Was Nikola Tesla a scientist or engineer? These men didn’t stop at scientific research and ended up conceptualizing or engineering their inventions. Engineers are not only the ones bearing helmets and operating on construction sites. Data science vs data engineering. How about Edison? Or Da Vinci?

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

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.

Data Pipeline 52

Data Pipeline IT Data Metadata 52

Jesse Anderson

NOVEMBER 14, 2023

A Guest Post by Ole Olesen-Bagneux In this blog post I would like to describe a new data team, that I call ‘the data discovery team’. 1) The data discovery team must work on discovering the IT landscape. That is done via a careful examination of all metadata repositories describing data sources.

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Metadata Data Science Big Data Data 147

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

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

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

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?

Metadata 130

Metadata Business Intelligence Data Lake BI 130

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 Engineering Podcast

DECEMBER 29, 2022

In this episode she shares the strategic and tactical elements of how to make more effective use of the technical and organizational resources that are available to you for getting work done with data. Atlan is the metadata hub for your data ecosystem. Struggling with broken pipelines? Missing data? Missing data?

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Management Metadata Business Intelligence Data Lake 130

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Data Engineering Data engineering is a process by which data engineers make data useful.

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Data Engineering Data Engineer Engineering Hadoop 40

Data Engineering Podcast

OCTOBER 30, 2022

In this episode Amir Orad discusses the Sisense platform and how it facilitates the embedding of analytics and data insights in every aspect of organizational and end-user experiences. Atlan is the metadata hub for your data ecosystem. And don’t forget to thank them for their continued support of this show!

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Business Intelligence Metadata MongoDB MySQL 130