Data Engineering Podcast
MAY 7, 2023
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. What are some of the categories of attributes that need to be managed in a prototypical customer profile?
Data Engineering Podcast
AUGUST 13, 2022
In this episode founder Shayan Mohanty explains how he and his team are bringing software best practices and automation to the world of machine learning data preparation and how it allows data engineers to be involved in the process. Data stacks are becoming more and more complex. That’s where our friends at Ascend.io
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Monte Carlo
MARCH 28, 2024
In a nutshell, DataOps engineers are responsible not only for designing and building data pipelines, but iterating on them via automation and collaboration as well. But these figures are considerably higher than what the site lists for Data Specialists, and around $10,000 higher than the average salary of a Data Manager.
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.
Knowledge Hut
NOVEMBER 17, 2023
The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.
Databand.ai
JULY 19, 2023
Learn more in our detailed guide to data lineage visualization (coming soon) Integration with Multiple Data Sources Data lineage tools are designed to integrate with a wide range of data sources, including databases, data warehouses, and cloud-based data platforms.
RandomTrees
NOVEMBER 29, 2023
So, here the argument on what to use and where to use become an important topic to be considered and here we can rather focus on some of the adaptable and sensitive models and we begin to consider the data vaults’ technique. So, what is a data vault model or modelling approach? post which is the ML model trainings.
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