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Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics

Cloudera

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. Let’s transform the first mile of the data pipeline.

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Data Pipeline with Airflow and AWS Tools (S3, Lambda & Glue)

Towards Data Science

Today’s post follows the same philosophy: fitting local and cloud pieces together to build a data pipeline. And, when it comes to data engineering solutions, it’s no different: They have databases, ETL tools, streaming platforms, and so on — a set of tools that makes our life easier (as long as you pay for them).

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6 Best Snowflake ETL Tools For 2023

Hevo

Are you trying to better understand the plethora of ETL tools available in the market to see if any of them fits your bill? Are you a Snowflake customer (or planning on becoming one) looking to extract and load data from a variety of sources? If any of the above questions apply to you, then […]

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What is a Data Pipeline?

Grouparoo

As a result, data has to be moved between the source and destination systems and this is usually done with the aid of data pipelines. What is a Data Pipeline? A data pipeline is a set of processes that enable the movement and transformation of data from different sources to destinations.

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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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Data Pipeline vs. ETL: Which Delivers More Value?

Ascend.io

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. However, they are not just an upgraded version of ETL. Yet, the technical problem is the same.

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Complete Guide to Data Transformation: Basics to Advanced

Ascend.io

Tools like Python’s requests library or ETL/ELT tools can facilitate data enrichment by automating the retrieval and merging of external data. Engineers are now embedding natural language models into data pipelines to further enhance automation and usability.