Grouparoo

OCTOBER 26, 2021

As a result, data has to be moved between the source and destination systems and this is usually done with the aid of data pipelines. What is a Data Pipeline? A data pipeline is a set of processes that enable the movement and transformation of data from different sources to destinations.

Data Pipeline 52

Data Pipeline ETL Tools ETL System Data Warehouse 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Data Engineering Podcast

DECEMBER 16, 2018

As the organization grows and gains more customers, the requirements for that pipeline will change. In this episode Christian Heinzmann, Head of Data Warehousing at Grubhub, discusses the various requirements for data pipelines and how the overall system architecture evolves as more data is being processed.

Data Pipeline 100

Data Pipeline Data Lake Data Warehouse Python 100

Ascend.io

APRIL 12, 2023

From this research, we developed a framework with a sequence of stages to implement data integrity quickly and measurably via data pipelines. Table of Contents Why does data integrity matter? At every level of a business, individuals must trust the data, so they can confidently make timely decisions. Let’s explore!

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape. Let’s take a closer look.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Christophe Blefari

JANUARY 20, 2024

Then here a list of global resources that can help you navigate through the field: The Data Engineer Roadmap — An image with advices and technology names to watch. Reddit r/dataengineering wiki a place where some data eng definitions are written. You'll be also asked to put in place a data infrastructure.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Podcast

DECEMBER 4, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Lake 100

Data Lake MongoDB MySQL Data Warehouse 100

Data Engineering Podcast

DECEMBER 11, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Monitoring data quality, tracing incidents, and testing changes can be daunting and often takes hours to days or even weeks. RudderStack helps you build a customer data platform on your warehouse or data lake.

Database 100

Database MySQL Data Lake MongoDB 100

Data Engineering Podcast

MAY 22, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. Stop struggling to speed up your data lake.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Towards Data Science

OCTOBER 20, 2023

An End-To-End Tutorial for Beginners Continue reading on Towards Data Science »

Data Pipeline 77

Data Pipeline MySQL Building Data Science 77

Data Engineering Weekly

MARCH 3, 2024

link] Zendesk: dbt at Zendesk The Zendesk team shares their journey of migrating legacy data pipelines to dbt, focusing on making them more reliable, efficient, and scalable. link] Martin Chesbrough: How to Build a Modern Data Team? This approach helps maintain accuracy, relevance, and compliance in generative AI applications.

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

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.

Architecture 130

Architecture Technology Google Cloud Metadata 130

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. Use VDK to build a data lake and merge multiple sources.

Data Lake 88

Data Lake Data SQL Data Warehouse 88

Ascend.io

APRIL 22, 2024

The Evolution of Data Engineering Over the past decade, we’ve seen tremendous change in the data engineering landscape. As companies scale their data and analytics capabilities, their data pipelines and operations have grown increasingly complex. Most of this data is never collected, and lost forever.

Project 52

Project Metadata Data Pipeline Data Engineering 52

Knowledge Hut

MARCH 28, 2024

They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

JANUARY 28, 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 Lake 147

Data Lake Building High Quality Data AWS 147

Knowledge Hut

NOVEMBER 17, 2023

As Azure Data Engineers, they'll be responsible for creating and looking after solutions that use data to help the company. They enhance data pipelines, transform data, and guarantee the accuracy, integrity, and compliance of the data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Podcast

DECEMBER 4, 2022

Especially once they realize 90% of all major data sources like Google Analytics, Salesforce, Adwords, Facebook, Spreadsheets, etc., Hevo Data is a highly reliable and intuitive data pipeline platform used by data engineers from 40+ countries to set up and run low-latency ELT pipelines with zero maintenance.

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

WeCloudData

OCTOBER 19, 2021

The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard. The client intends to build on and improve this data pipeline by moving towards a more serverless architecture and adding DevOps tools & workflows.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard. The client intends to build on and improve this data pipeline by moving towards a more serverless architecture and adding DevOps tools & workflows.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Data Engineering Podcast

MAY 8, 2022

Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake.

Database 100

Database Data Lake BI Business Intelligence 100

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Christophe Blefari

FEBRUARY 24, 2023

Coding patterns in Python — Startdatengineering is one of the best data engineering related blog and this time he propose a few patterns you might need to implement in Python when doing data pipelines. Data Economy 💰 Qbeast raises €2.5m

Kafka 130

Kafka Data Lake Data Storage Data 130

Databand.ai

JULY 5, 2023

What Are Data Observability Tools? Data observability tools are software solutions that oversee, analyze, and improve the performance of data pipelines. Data observability tools allow teams to detect issues such as missing values, duplicate records, or inconsistent formats early on before they affect downstream processes.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Data Engineering Podcast

NOVEMBER 6, 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.

MongoDB 130

MongoDB Scala MySQL Data Lake 130

Cloudera

JUNE 2, 2022

Over the last decade, we have often heard about the proliferation of data creating sources (mobile applications, laptops, sensors, enterprise apps) in heterogeneous environments (cloud, on-prem, edge) resulting in the exponential growth of data being created.

Systems 98

Systems Data Lake Google Cloud Data Collection 98

Monte Carlo

MARCH 4, 2024

Made For The Lakehouse: Iceberg and Delta There was a point in time not too long ago that data lake vs. data warehouse was a heated and important debate. Most major data cloud providers support both use cases. Data pipelines and architectures are evolving rapidly.

Metadata 52

Metadata Data Lake Data Warehouse Data Engineering 52

Towards Data Science

FEBRUARY 6, 2024

Order snapshots are stored in my own development area (image by the author) To prevent my extractions from impacting performance on the operational side, I queried this data regularly and stored it in a persistent staging area (PSA) within my data warehouse.

Systems 84

Systems Raw Data Metadata Data Cleanse 84

Edureka

FEBRUARY 7, 2023

Azure Data Engineers use a variety of Azure data services, such as Azure Synapse Analytics, Azure Data Factory, Azure Stream Analytics, and Azure Databricks, to design and implement data solutions that meet the needs of their organization. Gain hands-on experience using Azure data services.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Data Engineering Podcast

OCTOBER 9, 2022

Especially once they realize 90% of all major data sources like Google Analytics, Salesforce, Adwords, Facebook, Spreadsheets, etc., Hevo Data is a highly reliable and intuitive data pipeline platform used by data engineers from 40+ countries to set up and run low-latency ELT pipelines with zero maintenance.

Metadata 100

Metadata MongoDB AWS MySQL 100

Data Engineering Podcast

AUGUST 21, 2022

Go to dataengineeringpodcast.com/atlan today to learn more about how Atlan’s active metadata platform is helping pioneering data teams like Postman, Plaid, WeWork & Unilever achieve extraordinary things with metadata and escape the chaos. RudderStack helps you build a customer data platform on your warehouse or data lake.

Metadata 100

Metadata MongoDB MySQL Data Lake 100

Grouparoo

OCTOBER 6, 2021

Themes I was drawn to the articles that speak to a theme in the data world that I am passionate about: how data pipelines and data team practices are evolving to be more like traditional product development. 7 Be Intentional About the Batching Model in Your Data Pipelines Different batching models.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Monte Carlo

DECEMBER 29, 2022

No one wants to read marketing fluff, especially not data engineers. Everyone understands that data lineage and data pipeline monitoring are important, but the real question is, “how do you build it?” Building Spark Lineage For Data Lakes Everyone writes about the successful projects, but you learn more from the failures.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52