Remove Aggregated Data Remove Data Pipeline Remove ETL Tools
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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

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Complete Guide to Data Transformation: Basics to Advanced

Ascend.io

Intermediate Data Transformation Techniques Data engineers often find themselves in the thick of transforming data into formats that are not only usable but also insightful. Intermediate data transformation techniques are where the magic truly begins.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Some of the common challenges with data ingestion in Hadoop are parallel processing, data quality, machine data on a higher scale of several gigabytes per minute, multiple source ingestion, real-time ingestion and scalability. Flume has a simple event driven pipeline architecture with 3 important roles-Source, Channel and Sink.

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Azure Data Factory vs AWS Glue-The Cloud ETL Battle

ProjectPro

A survey by Data Warehousing Institute TDWI found that AWS Glue and Azure Data Factory are the most popular cloud ETL tools with 69% and 67% of the survey respondents mentioning that they have been using them. AWS Glue provides the functionality required by enterprises to build ETL pipelines.

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Tips to Build a Robust Data Lake Infrastructure

DareData

The architecture of a data lake project may contain multiple components, including the Data Lake itself, one or multiple Data Warehouses or one or multiple Data Marts. The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business. The main duties of an Azure Data Engineer are planning, developing, deploying, and managing the data pipelines.

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Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

A company’s production data, third-party ads data, click stream data, CRM data, and other data are hosted on various systems. An ETL tool or API-based batch processing/streaming is used to pump all of this data into a data warehouse. The following diagram explains how integrations work.