Remove Data Architecture Remove ETL Tools Remove Metadata Remove Unstructured Data
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Moving Past ETL and ELT: Understanding the EtLT Approach

Ascend.io

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. However , to reduce the impact on the business, a data warehouse remains in use.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Technical Data Engineer Skills 1.Python Knowing how to work with key-value pairs and object formats is still necessary.

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How to Become a Big Data Engineer in 2023

ProjectPro

Becoming a Big Data Engineer - The Next Steps Big Data Engineer - The Market Demand An organization’s data science capabilities require data warehousing and mining, modeling, data infrastructure, and metadata management. Most of these are performed by Data Engineers.

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

This way, Delta Lake brings warehouse features to cloud object storage — an architecture for handling large amounts of unstructured data in the cloud. Besides that, it’s fully compatible with various data ingestion and ETL tools. Databricks focuses on data engineering and data science.

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