phData

JUNE 14, 2023

In recent years, data engineering teams working with the Snowflake Data Cloud platform have embraced the continuous integration/continuous delivery (CI/CD) software development process to develop data products and manage ETL/ELT workloads more efficiently.

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Data Pipeline Database SQL Data Engineering 52

IBM Journey to AI blog

MAY 15, 2024

Two of the more popular methods, extract, transform, load (ETL ) and extract, load, transform (ELT) , are both highly performant and scalable. Data engineers build data pipelines, which are called data integration tasks or jobs, as incremental steps to perform data operations and orchestrate these data pipelines in an overall workflow.

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phData

FEBRUARY 14, 2023

This may result in data inconsistency when UPDATE and DELETE operations are performed on the target database. Matllion can replicate data from sources such as APIs, applications, relational databases, files, and NoSQL databases. For those looking to migrate to Snowflake who prefer using AWS services, DMS is a great solution.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Data Science Blog

SEPTEMBER 19, 2023

By automating the provisioning and management of cloud resources through code, IaC brings a host of advantages to the development and maintenance of Data Warehouse Systems in the cloud. So why using IaC for Cloud Data Infrastructures? appeared first on Data Science Blog.

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The MLOps Blog

MAY 17, 2023

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

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ETL Data Pipeline ML ML 59

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. And it injects mature process control techniques from the world of traditional engineering. Take a look at figure 1 below.

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DataOps Data Pipeline Data Engineering Data Engineer 52

phData

JANUARY 5, 2023

Python is the top programming language used by data engineers in almost every industry. Python has proven proficient in setting up pipelines, maintaining data flows, and transforming data with its simple syntax and proficiency in automation. Truly a must-have tool in your data engineering arsenal!

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Python Data Engineering Data Engineer Data Engineering 52