Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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Data Science Dojo

JULY 6, 2023

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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Analytics Vidhya

FEBRUARY 20, 2023

Introduction Azure data factory (ADF) is a cloud-based data ingestion and ETL (Extract, Transform, Load) tool. The data-driven workflow in ADF orchestrates and automates data movement and data transformation.

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The MLOps Blog

MAY 17, 2023

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

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Dataversity

SEPTEMBER 27, 2021

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. extract, transform, load) projects are often devoid of automated testing.

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Pickl AI

APRIL 9, 2025

Summary: This guide explores the top list of ETL tools, highlighting their features and use cases. It provides insights into considerations for choosing the right tool, ensuring businesses can optimize their data integration processes for better analytics and decision-making. What is ETL? What are ETL Tools?

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Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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Pickl AI

OCTOBER 17, 2024

Summary: This article explores the significance of ETL Data in Data Management. It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making.

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Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. Introduction The ETL process is crucial in modern data management.

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phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. Understanding the Basics What is a Data Warehouse?

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Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

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ODSC - Open Data Science

FEBRUARY 19, 2025

In the world of AI-driven data workflows, Brij Kishore Pandey, a Principal Engineer at ADP and a respected LinkedIn influencer, is at the forefront of integrating multi-agent systems with Generative AI for ETL pipeline orchestration. ETL ProcessBasics So what exactly is ETL? What is an Agent?

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phData

MARCH 14, 2024

In the data analytics processes, choosing the right tools is crucial for ensuring efficiency and scalability. Two popular players in this area are Alteryx Designer and Matillion ETL , both offering strong solutions for handling data workflows with Snowflake Data Cloud integration.

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Pickl AI

OCTOBER 15, 2024

Summary: Selecting the right ETL platform is vital for efficient data integration. Consider your business needs, compare features, and evaluate costs to enhance data accuracy and operational efficiency. Introduction In today’s data-driven world, businesses rely heavily on ETL platforms to streamline data integration processes.

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Dataconomy

JULY 29, 2024

Ed explained the differences between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes, highlighting the advantages of the ELT approach in modern data environments. He introduced Airflow as a robust tool for orchestrating data pipelines and DBT for data transformation within data warehouses.

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Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

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Dataversity

AUGUST 30, 2021

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. extract, transform, load) projects are often devoid of automated testing.

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phData

MARCH 8, 2023

Fivetran is used by businesses to centralize data from various sources into a single, comprehensive data warehouse. It allows organizations to easily connect their disparate data sources without having to manage any infrastructure. Building data pipelines manually is an expensive and time-consuming process.

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IBM Journey to AI blog

OCTOBER 22, 2024

This adaptability allows organizations to align their data integration efforts with distinct operational needs, enabling them to maximize the value of their data across diverse applications and workflows. This strategy helps organizations optimize data usage, expand into new markets, and increase revenue.

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Women in Big Data

OCTOBER 9, 2024

The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline? A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake.

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. This is where Fivetran and the Modern Data Stack come in.

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phData

NOVEMBER 9, 2023

This data mesh strategy combined with the end consumers of your data cloud enables your business to scale effectively, securely, and reliably without sacrificing speed-to-market. What is a Cloud Data Warehouse? For example, most data warehouse workloads peak during certain times, say during business hours.

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phData

JUNE 14, 2023

In recent years, data engineering teams working with the Snowflake Data Cloud platform have embraced the continuous integration/continuous delivery (CI/CD) software development process to develop data products and manage ETL/ELT workloads more efficiently.

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phData

SEPTEMBER 2, 2024

Best practices are a pivotal part of any software development, and data engineering is no exception. This ensures the data pipelines we create are robust, durable, and secure, providing the desired data to the organization effectively and consistently. What Are Matillion Jobs and Why Do They Matter?

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phData

FEBRUARY 3, 2023

More and more businesses are looking to better leverage their outsourced call center data to make more data-driven decisions. To do this on your own, you would need to create a data warehouse, optimize the reporting performance, and very clearly visualize the data. Another way to think of it is as Data Activation.

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Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Reverse ETL tools. Data orchestration tools. A Note on the Shift from ETL to ELT.

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The MLOps Blog

MARCH 15, 2023

In this post, you will learn about the 10 best data pipeline tools, their pros, cons, and pricing. A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process.

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Smart Data Collective

OCTOBER 17, 2022

Cloud data warehouses provide various advantages, including the ability to be more scalable and elastic than conventional warehouses. Can’t get to the data. All of this data might be overwhelming for engineers who struggle to pull in data sets quickly enough. Data pipeline maintenance.

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Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. ETL is vital for ensuring data quality and integrity.

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phData

NOVEMBER 28, 2023

In July 2023, Matillion launched their fully SaaS platform called Data Productivity Cloud, aiming to create a future-ready, everyone-ready, and AI-ready environment that companies can easily adopt and start automating their data pipelines coding, low-coding, or even no-coding at all. Why Does it Matter?

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phData

APRIL 28, 2025

For those unfamiliar with GIT or GIT practices, please refer Git for Business Users with Matillion DPC What is a Matillion Pipeline? A Matillion pipeline is a collection of jobs that extract, load, and transform (ETL/ELT) data from various sources into a target system, such as a cloud data warehouse like Snowflake.

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Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

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phData

APRIL 29, 2024

Understanding Fivetran Fivetran is a popular Software-as-a-Service platform that enables users to automate the movement of data and ETL processes across diverse sources to a target destination. For a longer overview, along with insights and best practices, please feel free to jump back to the previous blog.

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ODSC - Open Data Science

JANUARY 18, 2024

This individual is responsible for building and maintaining the infrastructure that stores and processes data; the kinds of data can be diverse, but most commonly it will be structured and unstructured data. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable.

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phData

OCTOBER 17, 2023

The story is all too common – a business user requests some data, the data team creates/prioritizes a ticket, and said ticket is completed after some number of months (or weeks if you’re lucky) – just to have the data be wrong, and the whole process starts again. Those are scary for data teams to change.

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