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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? What is Hadoop.

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The Evolution of Table Formats

Monte Carlo

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

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Data Catalog - A Broken Promise

Data Engineering Weekly

Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. I know that is an expensive statement to make😊 To be fair, I’m a big fan of data catalogs, or metadata management , to be precise.

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DataOps Tools: Key Capabilities & 5 Tools You Must Know About

Databand.ai

DataOps tools should provide a comprehensive data cataloging solution that allows organizations to create a centralized repository of their data assets, complete with metadata, data lineage information, and data samples.

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The Good and the Bad of Apache Airflow Pipeline Orchestration

AltexSoft

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. Metadata database.

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The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

Also, Databricks are pioneering the lakehouse concept that makes it possible to use data management features inherent in data warehousing on the raw data stored in a low-cost data lake owing to its metadata layer. Data orchestration involves managing the scheduling and execution of data workflows.

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Azure Data Engineer (DP-203) Certification Cost in 2023

Knowledge Hut

Why Should You Get an Azure Data Engineer Certification? Becoming an Azure data engineer allows you to seamlessly blend the roles of a data analyst and a data scientist. One of the pivotal responsibilities is managing data workflows and pipelines, a core aspect of a data engineer's role.