Ascend.io

OCTOBER 8, 2024

Data engineering is the backbone of any data-driven organization, responsible for building and maintaining the infrastructure that supports data collection, storage, and analysis. Traditionally, data engineers have focused on the technical aspects of data management, ensuring data pipelines run smoothly and efficiently.

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Data Engineering Podcast

OCTOBER 28, 2021

He also explains why he started Decodable to address that limitation and the work that he and his team have done to let data engineers build streaming pipelines entirely in SQL. What are the complexities that data engineers encounter when building pipelines on streaming systems?

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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. S3 is the state-of-the-art software system of our age. However, is that all enough?

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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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Knowledge Hut

JULY 5, 2024

Large enterprises heavily rely on data for informed decision-making, and this reliance is where data engineers step in. Data engineers like myself play a pivotal role in assessing infrastructure and taking relevant actions. Looking ahead, the future of data engineering appears promising.

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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.

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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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Data Engineering Podcast

JUNE 1, 2021

Summary Every part of the business relies on data, yet only a small team has the context and expertise to build and maintain workflows and data pipelines to transform, clean, and integrate it. RudderStack’s smart customer data pipeline is warehouse-first. What are the main goals that you have for Shipyard?

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Data Engineering Podcast

JULY 17, 2022

In this episode Crux CTO Mark Etherington discusses the different costs involved in managing external data, how to think about the total return on investment for your data, and how the Crux platform is architected to reduce the toil involved in managing third party data. Tired of deploying bad data?

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Data Engineering Podcast

APRIL 19, 2021

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

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Data Engineering Podcast

FEBRUARY 18, 2024

In this episode Dain Sundstrom, CTO of Starburst, explains how the combination of the Trino query engine and the Iceberg table format offer the ease of use and execution speed of data warehouses with the infinite storage and scalability of data lakes. Data lakes are notoriously complex. Your first 30 days are free!

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Data Engineering Podcast

JANUARY 30, 2022

Summary The Data Engineering Podcast has been going for five years now and has included conversations and interviews with a huge number of guests, covering a broad range of topics. In this episode he shares some reflections on producing the podcast, compiling the book, and relevant trends in the ecosystem of data engineering.

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Databand.ai

JUNE 8, 2023

Observability in Your Data Pipeline: A Practical Guide Eitan Chazbani June 8, 2023 Achieving observability for data pipelines means that data engineers can monitor, analyze, and comprehend their data pipeline’s behavior. This is part of a series of articles about data observability.

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Data Engineering Podcast

MAY 18, 2024

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. My thanks to the team at Code Comments for their support.

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Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Your newly mimicked datasets are safe to share with developers, QA, data scientists—heck, even distributed teams around the world. What do you have planned for the future of Profisee?

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Hevo

JUNE 7, 2024

Data pipelines play a vital role in modern data management. They connect various data sources within an organization to those who need them. The ability to move data quickly and efficiently allows for identifying patterns and new insights to aid in long-term planning and daily decision-making.

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Ascend.io

APRIL 28, 2023

Data pipelines are having a moment — at least, that is, within the data world. That’s because as more and more businesses are adopting a data-driven mindset, the movement of data into and within organizations has never been a bigger priority.

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Data Engineering Podcast

SEPTEMBER 30, 2019

Summary Building an end-to-end data pipeline for your machine learning projects is a complex task, made more difficult by the variety of ways that you can structure it. We have partnered with organizations such as O’Reilly Media, Dataversity, Corinium Global Intelligence, and Data Council.

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Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

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Ascend.io

AUGUST 29, 2023

A star-studded baseball team is analogous to an optimized “end-to-end data pipeline” — both require strategy, precision, and skill to achieve success. Just as every play and position in baseball is key to a win, each component of a data pipeline is integral to effective data management.

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Data Engineering Podcast

APRIL 7, 2019

Summary How much time do you spend maintaining your data pipeline? This was a fascinating conversation with someone who has spent his entire career working on simplifying complex data problems. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference.

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Data Engineering Podcast

JANUARY 26, 2020

Summary Data pipelines are complicated and business critical pieces of technical infrastructure. You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data management.

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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.

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Data Engineering Podcast

SEPTEMBER 19, 2021

This brings with it a unique set of challenges for data collection, data management, and analytical capabilities. In this episode Jillian Rowe shares her experience of working in the field and supporting teams of scientists and analysts with the data infrastructure that they need to get their work done. Missing data?

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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. Go to dataengineeringpodcast.com/dagster today to get started.

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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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Meltano

OCTOBER 5, 2022

Interested in becoming a data engineer? The need for data experts in the U.S. job market is expected to grow by 22% in this decade, and according to LinkedIn’s 2020 report , a data engineer is listed as the 8th fastest growing job today. But what is data engineering exactly and what does a data engineer do?

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Data Engineering Podcast

JUNE 23, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Data lakes in various forms have been gaining significant popularity as a unified interface to an organization's analytics.

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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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Data Engineering Weekly

JUNE 12, 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. Sign up free to test out the tool today. Is there a bottleneck?

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Netflix Tech

FEBRUARY 9, 2022

JAR) form to be executed as part of the user defined data pipeline. data pipeline ?—?a DAG) for the purpose of transforming data using some business logic. Netflix homegrown CLI tool for data pipeline management. SQL) or compiled (e.g. Dataflow ?—?Netflix namespace ? workflow ?—?see

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Data Engineering Weekly

DECEMBER 21, 2022

We went through a full cycle that “schema-on-read ” led to the infamous GIGO (Garbage In, Garbage Out) problem in data lakes, as noted in this What Happened To Hadoop retrospect. The Data world Before Hadoop Era We must walk through memory lane to understand why functional data engineering is critical.

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Knowledge Hut

NOVEMBER 17, 2023

Azure Data Engineers play an important role in building efficient, secure, and intelligent data solutions on Microsoft Azure's powerful platform. The position of Azure Data Engineers is becoming increasingly important as businesses attempt to use the power of data for strategic decision-making and innovation.

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Data Engineering Podcast

MARCH 24, 2024

In this episode Pete Hunt, CEO of Dagster labs, outlines these new capabilities, how they reduce the burden on data teams, and the increased collaboration that they enable across teams and business units. Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started. Your first 30 days are free!

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Data Engineering Podcast

JUNE 16, 2024

In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform. Can you describe what role Trino and Iceberg play in Stripe's data architecture?

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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.

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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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