François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services.

Technology 130

Technology Architecture Google Cloud Metadata 130

Data Engineering Podcast

APRIL 14, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is brought to you by Datafold – a testing automation platform for data engineers that prevents data quality issues from entering every part of your data workflow, from migration to dbt deployment.

Non-relational Database 147

Non-relational Database Relational Database Database Designing 147

Data Engineering Podcast

APRIL 21, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 182

Data Lake High Quality Data Data Pipeline Machine Learning 182

Data Engineering Podcast

APRIL 28, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Building 147

Building Data Lake High Quality Data Machine Learning 147

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?

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

Data Engineering Podcast

JUNE 9, 2024

Data lakes are notoriously complex. How much of the complexity is due to the nature of streaming data vs. the architectural realities of Flink? How has the lack of visibility into the flow of data in Flink impacted the ways that teams think about where/when/how to apply it? Data lakes are notoriously complex.

Process 147

Process Data Lake High Quality Data Machine Learning 147

Data Engineering Podcast

MARCH 31, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Project 130

Project Data Lake High Quality Data Data Workflow 130

Data Engineering Podcast

MAY 5, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Building 147

Building Data Lake High Quality Data Machine Learning 147

Data Engineering Podcast

MARCH 24, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 162

Data Lake High Quality Data Hadoop Data Pipeline 162

Data Engineering Podcast

JANUARY 21, 2024

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. How has that changed the architectural approach to CDPs? Want to see Starburst in action?

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Data Engineering Podcast

JANUARY 7, 2024

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Data Process 147

Data Process Process Data Lake High Quality Data 147

Data Engineering Podcast

FEBRUARY 25, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Database 162

Database Technology Data Lake High Quality Data 162

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. Can you describe the architecture of Nessie?

Data Lake 147

Data Lake High Quality Data Architecture Data Pipeline 147

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

DECEMBER 3, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. Datafold has recently launched a 3-in-1 product experience to support accelerated data migrations. Data lakes are notoriously complex.

Systems 130

Systems Designing Data Lake SQL 130

Data Engineering Podcast

FEBRUARY 11, 2024

In this episode Andrew Jefferson explains the complexities of building a robust system for data sharing, the techno-social considerations, and how the Bobsled platform that he is building aims to simplify the process. Want to see Starburst in action?

Data Lake 147

Data Lake High Quality Data Government Data Pipeline 147

Data Engineering Podcast

MARCH 3, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

Data Engineering Podcast

DECEMBER 31, 2023

In this episode Andrey Korchack, CTO of fintech startup Monite, discusses the complexities of designing and implementing a data platform in that sector. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Designing 130

Designing Data Lake High Quality Data SQL 130

Data Engineering Podcast

NOVEMBER 19, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. Data lakes are notoriously complex. Materialize]([link] You shouldn't have to throw away the database to build with fast-changing data.

Project 147

Project Data Lake High Quality Data SQL 147

Data Engineering Podcast

DECEMBER 17, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. Data lakes are notoriously complex. Materialize]([link] You shouldn't have to throw away the database to build with fast-changing data.

Data Lake 130

Data Lake High Quality Data SQL Architecture 130

Data Engineering Podcast

NOVEMBER 5, 2023

Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack You shouldn't have to throw away the database to build with fast-changing data. Data lakes are notoriously complex. Materialize]([link] You shouldn't have to throw away the database to build with fast-changing data.

PostgreSQL 147

PostgreSQL Data Lake High Quality Data SQL 147

Data Engineering Podcast

NOVEMBER 12, 2023

If you are migrating to a modern data stack, Datafold can also help you automate data and code validation to speed up the migration. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold Data lakes are notoriously complex. With Materialize, you can! Sponsored By: Starburst : ![Starburst

Software Engineering 147

Software Engineering Software Engineer Engineering Data Lake 147

Data Engineering Podcast

DECEMBER 10, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management You shouldn't have to throw away the database to build with fast-changing data. Data lakes are notoriously complex. With Materialize, you can! That’s three free boards at dataengineeringpodcast.com/miro.

Data Lake 130

Data Lake High Quality Data SQL Architecture 130

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. It was designed to support high-volume data exchange and compatibility across different system versions, which is essential for streaming architectures such as Apache Kafka.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Weekly

DECEMBER 25, 2023

Integrating AI into data workflows is not just a trend but a paradigm shift, making data processes more efficient and intelligent. Lake House Architectures: The New Frontier Lakehouse architectures have been at the forefront of data engineering discussions this year.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Knowledge Hut

MARCH 28, 2024

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

Data Engineering Podcast

JULY 3, 2022

In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

SEPTEMBER 11, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control.

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Knowledge Hut

NOVEMBER 17, 2023

They enhance data pipelines, transform data, and guarantee the accuracy, integrity, and compliance of the data. Their job entails Azure data engineer skills like using big data, databases, data lakes, and analytics to help firms make efficient data-driven decisions.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Lake 52

Data Engineering Weekly

JANUARY 15, 2023

. 🎯 I defined the modern data stack sometime back as; @sarahmk125 MDS is a set of vendor tools that solve niche data problems (lineage, orchestration, quality) with the side effect of creating a disjointed data workflow that makes data folks lives more complicated.","username":"ananthdurai","name":"at-ananth-at-data-folks

Data Engineer 52

Data Engineer Data Engineering Engineering Metadata 52

Knowledge Hut

NOVEMBER 2, 2023

To create effective and scalable data pipelines, data storage solutions, and data analytics environments, they work with a variety of Azure services and tools. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineer 52

Data Engineer Data Engineering Project Coding 52

DataKitchen

JANUARY 25, 2022

When an especially gifted data engineer decided to leave, it left the team scrambling to support routine functions. The dynamic nature of the consulting team meant that architectural decisions made at the data engineering level were often short-sighted and incoherent.

Consulting 97

Consulting Recruitment Data Lake Data Engineer 97

Ascend.io

DECEMBER 21, 2022

By harnessing the power of Ascend and Snowflake, data teams can now ingest any data from any location, and in just minutes begin releasing entirely new data products. “We’re here to help our customers focus on the data transformation that produces real value, not just busywork.

Data Ingestion 52

Data Ingestion Google Cloud Data Lake Cloud 52