Remove Data Pipeline Remove ETL Tools Remove Unstructured Data
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Why Modernizing the First Mile of the Data Pipeline Can Accelerate all Analytics

Cloudera

Every enterprise is trying to collect and analyze data to get better insights into their business. 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.

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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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The Role of an AI Data Quality Analyst

Monte Carlo

Let’s dive into the responsibilities, skills, challenges, and potential career paths for an AI Data Quality Analyst today. Table of Contents What Does an AI Data Quality Analyst Do? Tools : Familiarity with data validation tools, data wrangling tools like Pandas , and platforms such as AWS , Google Cloud , or Azure.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

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Moving Past ETL and ELT: Understanding the EtLT Approach

Ascend.io

In this article, we assess: The role of the data warehouse on one hand, and the data lake on the other; The features of ETL and ELT in these two architectures; The evolution to EtLT; The emerging role of data pipelines. However , to reduce the impact on the business, a data warehouse remains in use.

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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

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?