Data Lake Data Warehouse ETL Tools Relational Database 
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
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. Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer.
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Grouparoo
OCTOBER 26, 2021
Origin The origin of a data pipeline refers to the point of entry of data into the pipeline. This includes the different possible sources of data such as application APIs, social media, relational databases, IoT device sensors, and data lakes. featured image via unsplash
Knowledge Hut
SEPTEMBER 26, 2023
We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. ETL activities are also the responsibility of data engineers.
Knowledge Hut
NOVEMBER 28, 2023
Kafka is great for ETL and provides memory buffers that provide process reliability and resilience. ETL is central to getting your data where you need it. Relational database management systems (RDBMS) remain the key to data discovery and reporting, regardless of their location.
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.
AltexSoft
AUGUST 4, 2021
Now let’s think of sweets as the data required for your company’s daily operations. Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit.
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