The Best ETL Tools in 2021
KDnuggets
DECEMBER 21, 2021
If you have clear, well-defined objectives, it won’t be hard to identify the ETL technology that best meets your needs. Here are some of the best ETL tools you can use in your business.
ETL Related Topics 
Good ETL Practices with Apache Airflow
Analytics Vidhya
NOVEMBER 30, 2021
Introduction to ETL ETL is a type of three-step data integration: Extraction, Transformation, Load are processing, used to combine data from multiple sources. The post Good ETL Practices with Apache Airflow appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.
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What Does ETL Have to Do with Machine Learning?
KDnuggets
AUGUST 15, 2022
ETL during the process of producing effective machine learning algorithms is found at the base - the foundation. Let’s go through the steps on how ETL is important to machine learning.
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Why Do We Prefer ELT Rather than ETL in the Data Lake? What is the Difference between ETL & ELT
insideBIGDATA
JULY 4, 2023
In this article, Ashutosh Kumar discusses the emergence of modern data solutions that have led to the development of ELT and ETL with unique features and advantages. ELT is more popular due to its ability to handle large and unstructured datasets like in data lakes.
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ETL Pipeline with Google DataFlow and Apache Beam
Analytics Vidhya
JULY 29, 2022
Building an ETL pipeline using Apache […]. The post ETL Pipeline with Google DataFlow and Apache Beam appeared first on Analytics Vidhya. Introduction Processing large amounts of raw data from various sources requires appropriate tools and solutions for effective data integration.
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Building Your First ETL Pipeline with Bash
KDnuggets
JUNE 24, 2024
Bash is a good choice for ETL due to its simplicity, flexibility, automation capabilities, and interoperability with other CLI tools. Get more info on putting together your first ETL script using Bash mainstay components.
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A Complete Guide on Building an ETL Pipeline for Beginners
Analytics Vidhya
JUNE 13, 2022
Introduction on ETL Pipeline ETL pipelines are a set of processes used to transfer data from one or more sources to a database, like a data warehouse. The post A Complete Guide on Building an ETL Pipeline for Beginners appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.
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Best Practices for Building ETLs for ML
KDnuggets
OCTOBER 12, 2023
This article talks about several best practices for writing ETLs for building training datasets. It delves into several software engineering techniques and patterns applied to ML.
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ETL and Workflow Orchestration Tools
Analytics Vidhya
AUGUST 24, 2022
Introduction In this article, we attempt to capture the complexity of ETL and workflow orchestration tools, which aid in better data management and control by providing multiple alternatives for performing various operations in discrete blocks while maintaining visibility and clear goals for each action. We’ll continue […].
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Data Integration: Strategies for Efficient ETL Processes
Analytics Vidhya
JUNE 3, 2024
This crucial process, called Extract, Transform, Load (ETL), involves extracting data from multiple origins, transforming it into a consistent format, and loading it into a target system for analysis.
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Building a Scalable ETL with SQL + Python
KDnuggets
APRIL 21, 2022
This post will look at building a modular ETL pipeline that transforms data with SQL and visualizes it with Python and R.
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ETL vs ELT in 2022: Do they matter?
Analytics Vidhya
AUGUST 5, 2022
The post ETL vs ELT in 2022: Do they matter? Obtaining, structuring, and analyzing these data into new, relevant information is crucial in today’s world. Since contextual data exposes popular patterns and trends, we have arrived at the stage where businesses take data-driven decisions to […]. appeared first on Analytics Vidhya.
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ETL Pipeline using Shell Scripting | Data Pipeline
Analytics Vidhya
JANUARY 5, 2022
Introduction ETL pipelines can be built from bash scripts. You will learn about how shell scripting can implement an ETL pipeline, and how ETL scripts or tasks can be scheduled using shell scripting. The post ETL Pipeline using Shell Scripting | Data Pipeline appeared first on Analytics Vidhya. What is shell scripting?
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Crafting Serverless ETL Pipeline Using AWS Glue and PySpark
Analytics Vidhya
DECEMBER 26, 2022
Overview ETL (Extract, Transform, and Load) is a very common technique in data engineering. Traditionally, ETL processes are […]. The post Crafting Serverless ETL Pipeline Using AWS Glue and PySpark appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.
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ETL & ELT – Data Engineering Essentials
Analytics Vidhya
APRIL 28, 2022
Introduction At the highest level, ETL converts your data before uploading, while ELT converts data only after uploading to your repository. In this post, we will take a closer look at the differences between the way ETL and ELT work to help you […]. This article was published as a part of the Data Science Blogathon.
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SQL and Data Integration: ETL and ELT
KDnuggets
JANUARY 19, 2023
In this article, we will discuss use cases and methods for using ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes along with SQL to integrate data from various sources.
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Implementing ETL Process Using Python to Learn Data Engineering
Analytics Vidhya
JUNE 27, 2021
The post Implementing ETL Process Using Python to Learn Data Engineering appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview: Assume the job of a Data Engineer, extracting data from.
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ETL Tools: A Brief Introduction
Analytics Vidhya
MAY 16, 2022
Introduction on ETL Tools The amount of data being used or stored in today’s world is extremely huge. The post ETL Tools: A Brief Introduction appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. While handling this huge amount of data, one has to […].
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Pandas Vs PETL for ETL
Analytics Vidhya
MAY 30, 2021
ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction to ETL ETL as the name suggests, Extract Transform and. The post Pandas Vs PETL for ETL appeared first on Analytics Vidhya.
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Data Warehousing and ETL Best Practices
KDnuggets
FEBRUARY 27, 2023
How you can improve your data warehousing ETL process with these simple practices.
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Schedule & Run ETLs with Jupysql and GitHub Actions
KDnuggets
MAY 1, 2023
This blog provided you with a comprehensive overview of ETL and JupySQL, including a brief introduction to ETLs and JupySQL. We also demonstrated how to schedule an example ETL notebook via GitHub actions, which allows you to automate the process of executing ETLs and JupySQL from Jupyter.
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Unlock the True Potential of Your Data with ETL and ELT Pipeline
Analytics Vidhya
FEBRUARY 4, 2023
Introduction This article will explain the difference between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) when data transformation occurs. In ETL, data is extracted from multiple locations to meet the requirements of the target data file and then placed into the file.
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How We Performed ETL on One Billion Records For Under $1 With Delta Live Tables
databricks
APRIL 13, 2023
Today, Databricks sets a new standard for ETL (Extract, Transform, Load) price and performance. While customers have been using Databricks for their ETL.
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ELT vs ETL: Unveiling the Differences and Similarities
Analytics Vidhya
AUGUST 22, 2023
Two prominent methodologies have emerged to facilitate this process: Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT).
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The Ultimate Guide To Setting-Up An ETL (Extract, Transform, and Load) Process Pipeline
Analytics Vidhya
NOVEMBER 1, 2021
This article was published as a part of the Data Science Blogathon What is ETL? ETL is a process that extracts data from multiple source systems, changes it (through calculations, concatenations, and so on), and then puts it into the Data Warehouse system. ETL stands for Extract, Transform, and Load.
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Apache Airflow used for Performing ETL
Analytics Vidhya
JULY 18, 2022
The post Apache Airflow used for Performing ETL appeared first on Analytics Vidhya. For example, they extract, transform and load data from various sources into their data warehouse. Sources include customer transactions, data from Software as a Service (SAAS) offerings, […].
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15 Best ETL Tools Available in the Market in 2023
Analytics Vidhya
AUGUST 18, 2023
Introduction In the era of Data storehouse, the need for assimilating the data from contrasting sources into a single consolidated database requires you to Extract the data from its parent source, Transform and amalgamate it, and thus, Load it into the consolidated database (ETL).
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Introduction to Data Engineering- ETL, Star Schema and Airflow
Analytics Vidhya
SEPTEMBER 1, 2021
The post Introduction to Data Engineering- ETL, Star Schema and Airflow appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon A data scientist’s ability to extract value from data is closely related to how well-developed a company’s data storage and processing infrastructure is.
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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud
NOVEMBER 27, 2024
While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. Create dbt models in dbt Cloud.
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Difference between ETL and ELT Pipeline
Analytics Vidhya
MARCH 16, 2023
Users of Oozie can describe dependencies between various jobs […] The post Difference between ETL and ELT Pipeline appeared first on Analytics Vidhya. It enables users to plan and carry out complex data processing workflows while handling several tasks and operations throughout the Hadoop ecosystem.
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Building an ETL Data Pipeline Using Azure Data Factory
Analytics Vidhya
JUNE 15, 2022
Introduction ETL is the process that extracts the data from various data sources, transforms the collected data, and loads that data into a common data repository. The post Building an ETL Data Pipeline Using Azure Data Factory appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.
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ETL vs ELT: Which One is Right for Your Data Pipeline?
KDnuggets
MARCH 31, 2023
Learn about the differences between ETL and ELT data integration techniques and determine which is right for your data pipeline.
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AWS Glue: Simplifying ETL Data Processing
Analytics Vidhya
DECEMBER 28, 2022
Source: [link] Introduction If you are familiar with databases, or data warehouses, you have probably heard the term “ETL.” The post AWS Glue: Simplifying ETL Data Processing appeared first on Analytics Vidhya. As the amount of data at organizations grow, making use of that data in analytics to derive business insights grows as well.
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Future trends in ETL
Dataconomy
FEBRUARY 12, 2024
The acronym ETL—Extract, Transform, Load—has long been the linchpin of modern data management, orchestrating the movement and manipulation of data across systems and databases. However, the exponential growth in data volume, velocity, and variety is challenging the traditional paradigms of ETL, ushering in a transformative era.
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Open Source Python ETL
Hacker News
JUNE 18, 2024
Amphi is a micro ETL designed for extracting, preparing and cleaning data from various sources and formats. Develop data pipelines and generate native Python code you can deploy anywhere.
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Evolution in ETL: How Skipping Transformation Enhances Data Management
KDnuggets
DECEMBER 12, 2023
This article provides an overview of two new data preparation techniques that enable data democratization while minimizing transformation burdens.
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Serverless High Volume ETL data processing on Code Engine
IBM Data Science in Practice
JANUARY 13, 2025
By Santhosh Kumar Neerumalla , Niels Korschinsky & Christian Hoeboer Introduction This blogpost describes how to manage and orchestrate high volume Extract-Transform-Load (ETL) loads using a serverless process based on Code Engine. Thus, we use an Extract-Transform-Load (ETL) process to ingest the data.
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Developing Robust ETL Pipelines for Data Science Projects
NOVEMBER 15, 2024
In this article, we’ll look at how to build ETL pipelines for data science projects.
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Transforming Your Data Pipeline with dbt(data build tool)
Analytics Vidhya
JUNE 14, 2024
In today’s data-driven world, extracting, transforming, and loading (ETL) data is crucial for gaining valuable insights. While many ETL tools exist, dbt (data build tool) is emerging as a game-changer. Introduction Have you ever struggled with managing complex data transformations?
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How I Redesigned over 100 ETL into ELT Data Pipelines
KDnuggets
NOVEMBER 15, 2021
Learn how to level up your Data Pipelines!
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Top Stories, Nov 15-21: 19 Data Science Project Ideas for Beginners
KDnuggets
NOVEMBER 23, 2021
Also: How I Redesigned over 100 ETL into ELT Data Pipelines; Where NLP is heading; Don’t Waste Time Building Your Data Science Network; Data Scientists: How to Sell Your Project and Yourself.
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Developing an End-to-End Automated Data Pipeline
Analytics Vidhya
JULY 20, 2022
Be it a streaming job or a batch job, ETL and ELT are irreplaceable. Before designing an ETL job, choosing optimal, performant, and cost-efficient tools […]. Introduction Data acclimates to countless shapes and sizes to complete its journey from a source to a destination.
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7 Data Engineering Tools for Beginners
KDnuggets
OCTOBER 3, 2024
Learn the data engineering tools for data orchestration, database management, batch processing, ETL (Extract, Transform, Load), data transformation, data visualization, and data streaming.
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