AltexSoft
AUGUST 29, 2023
In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?
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.
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Ascend.io
AUGUST 31, 2023
In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts.
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.
DataKitchen
JUNE 12, 2023
We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.
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. Data engineers should have a solid understanding of SQL for querying and managing data in relational databases.
ProjectPro
DECEMBER 7, 2021
Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.
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