Data Engineering Podcast

JULY 17, 2022

Summary There are extensive and valuable data sets that are available outside the bounds of your organization. Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. Atlan is the metadata hub for your data ecosystem.

Data Management 130

Data Management Management Metadata MongoDB 130

Ascend.io

AUGUST 22, 2023

Businesses are in a continuous race to harness data as a powerful propellant for innovation. Yet, the task of efficient and prompt data delivery remains a challenge. The demands of building, scaling, and maintaining data pipelines have grown increasingly complex and error-prone. What Are Automated Data Pipelines?

Data Pipeline 52

Data Pipeline Raw Data Bytes Transportation 52

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.

Data Pipeline 100

Data Pipeline Machine Learning Data Warehouse Datasets 100

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.

Data Pipeline 52

Data Pipeline Pipeline-centric Database-centric Data Ingestion 52

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.

Data Pipeline 100

Data Pipeline Data Warehouse Data Data Engineering 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.

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Data Pipeline SQL Data Architecture Data 78

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. They have built an easy to use platform that lets you leverage your company’s single sign on for your data platform.

Data Pipeline 100

Data Pipeline Pipeline-centric Database-centric AWS 100

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.

Data Pipeline 52

Data Pipeline Bytes Data Collection Raw Data 52

Ascend.io

JULY 28, 2023

Data pipelines are integral to business operations, regardless of whether they are meticulously built in-house or assembled using various tools. As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Ready to fortify your data management practice?

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

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.

Data Pipeline 100

Data Pipeline Machine Learning Media Data 100

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

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. Master Data Management (MDM) is the process of building consensus around what the information actually means in the context of the business and then shaping the data to match those semantics.

Data Management 100

Data Management Management MongoDB Scala 100

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.

Data Pipeline 52

Data Pipeline Data Data Warehouse Data Engineering 52

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. a set of tasks (or jobs) to be executed in a predefined order (a.k.a. Dataflow ?—?Netflix

Data Pipeline 82

Data Pipeline Management Scala Python 82

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.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Data Engineering Podcast

JANUARY 26, 2020

Summary Data pipelines are complicated and business critical pieces of technical infrastructure. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform.

Data Pipeline 100

Data Pipeline PostgreSQL Media Data Validation 100

Christophe Blefari

MARCH 15, 2024

Saying mainly that " Sora is a tool to extend creativity " Last point Mira has been mocked and criticised online because as a CTO she wasn't able to say on which public / licensed data Sora has been trained on. Pandera, a data validation library for dataframes, now supports Polars.

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Metadata Datasets Data Data Warehouse 272

Hevo

FEBRUARY 2, 2024

Data pipelines have become an integral part of organizational workflows to keep pace with the rapidly evolving landscape of data management and analytics. By systematically processing and transporting data from its source to its destination, data pipelines help with data-driven decision-making.

Data Pipeline 40

Data Pipeline Transportation Data Data Management 40

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Data Engineering Podcast

JUNE 16, 2024

Summary Stripe is a company that relies on data to power their products and business. 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.

Data Lake 147

Data Lake High Quality Data Metadata Machine Learning 147

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

Ascend.io

AUGUST 15, 2023

This same principle holds true in data management. It’s no surprise, then, that the quest for Fivetran alternatives is on the rise as organizations set their sights on a more holistic data approach. Defense: Saving Money with Intelligent Data Refresh In football, a solid defense does more than just stop goals.

Data Management 52

Data Management Management Data Ingestion Data Pipeline 52

Hevo

OCTOBER 9, 2024

Did you know that businesses lose more than $3 trillion a year due to inadequate data management, according to an IBM estimate1 from 2016? The need for effective data management methods has never been clearer as companies struggle with an ever-growing volume of data from many sources. Data […]

Data Pipeline 40

Data Pipeline Data Data Management Management 40

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

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

DECEMBER 16, 2018

Summary Every business needs a pipeline for their critical data, even if it is just pasting into a spreadsheet. As the organization grows and gains more customers, the requirements for that pipeline will change. Can you start by sharing your definition of a data pipeline? What are your thoughts on that approach?

Data Pipeline 100

Data Pipeline Data Lake Data Warehouse Designing 100

Ascend.io

MARCH 2, 2023

The system suffered frequent outages and regularly lost months of data. We couldn’t get data to the business fast enough, and the data we did ship wasn’t trustworthy. Our velocity of delivering new data products continued to diminish. The initial wave of work migrating 75 data projects is proceeding like clockwork!

Data Pipeline 52

Data Pipeline Media Portfolio Data Ingestion 52

Ascend.io

APRIL 12, 2023

Right now, at this moment, are you prepared to act on your company’s data? So when we talk about making data usable, we’re having a conversation about data integrity. Data integrity is the overall readiness to make confident business decisions with trustworthy data, repeatedly and consistently. If not, why?

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Data Engineering Podcast

JUNE 2, 2024

Summary Modern businesses aspire to be data driven, and technologists enjoy working through the challenge of building data systems to support that goal. Data governance is the binding force between these two parts of the organization. What are some of the misconceptions that you encounter about data governance?

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Data Governance Government Data Lake High Quality Data 147

Data Engineering Podcast

JUNE 30, 2024

Petr shares his journey from being an engineer to founding Synq, emphasizing the importance of treating data systems with the same rigor as engineering systems. He discusses the challenges and solutions in data reliability, including the need for transparency and ownership in data systems. Want to see Starburst in action?

Pipeline-centric 147

Pipeline-centric Engineering Data Lake High Quality Data 147

Data Engineering Podcast

NOVEMBER 16, 2020

Summary The core mission of data engineers is to provide the business with a way to ask and answer questions of their data. This often takes the form of business intelligence dashboards, machine learning models, or APIs on top of a cleaned and curated data set.

Data Management 100

Data Management Management BI Business Intelligence 100

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

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

Data Engineering Podcast

MAY 27, 2018

In this episode CTO and co-founder of Alooma, Yair Weinberger, explains how the platform addresses the common needs of data collection, manipulation, and storage while allowing for flexible processing. How do you manage the underlying infrastructure to support your SLA of 5 nines? What is Alooma and what is the origin story?

Data Pipeline 100

Data Pipeline MongoDB Google Cloud Scala 100

Data Engineering Podcast

JUNE 17, 2017

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. Can you start by giving an overview of your pipeline and the type of workload that you are optimizing for?

Data Pipeline 100

Data Pipeline Kafka Business Intelligence Architecture 100

Data Engineering Podcast

JUNE 25, 2023

Summary Data transformation is a key activity for all of the organizational roles that interact with data. Because of its importance and outsized impact on what is possible for downstream data consumers it is critical that everyone is able to collaborate seamlessly. Can you describe what SQLMesh is and the story behind it?

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Data Engineering Data Engineer Python Engineering 225

Data Engineering Podcast

MARCH 10, 2024

Summary Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between data lake and warehouse capabilities is the catalog. Data lakes are notoriously complex. Join us at the top event for the global data community, Data Council Austin.

Data Lake 147

Data Lake High Quality Data Data Pipeline Architecture 147