Analytics Vidhya

APRIL 23, 2024

Introduction Apache Airflow is a powerful platform that revolutionizes the management and execution of Extracting, Transforming, and Loading (ETL) data processes. It offers a scalable and extensible solution for automating complex workflows, automating repetitive tasks, and monitoring data pipelines.

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AWS ETL Data Pipeline Analytics 310

Analytics Vidhya

JANUARY 15, 2021

ArticleVideos I will admit, AWS Data Wrangler has become my go-to package for developing extract, transform, and load (ETL) data pipelines and other day-to-day. The post Using AWS Data Wrangler with AWS Glue Job 2.0 appeared first on Analytics Vidhya.

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AWS ETL Data Pipeline Analytics 264

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. The source data is unstructured JSON, while the target is a structured, relational database.

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ETL Data Pipeline Database Data Warehouse 100

Smart Data Collective

OCTOBER 17, 2022

Data pipelines automatically fetch information from various disparate sources for further consolidation and transformation into high-performing data storage. There are a number of challenges in data storage , which data pipelines can help address. The movement of data in a pipeline from one point to another.

Data Pipeline 145

Data Pipeline Data Warehouse ETL Data Lakes 145

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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ETL Hadoop Data Warehouse Data Pipeline 126

Flipboard

NOVEMBER 7, 2023

“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift.

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ETL Data Pipeline Machine Learning Machine Learning 181

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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Azure ETL Analytics Analytics 283

IBM Journey to AI blog

MAY 15, 2024

Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models. Unified, governed data can also be put to use for various analytical, operational and decision-making purposes. This process is known as data integration, one of the key components to a strong data fabric.

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Data Pipeline ETL SQL Database 85

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. Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

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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ETL Data Pipeline ML ML 59

Alation

MAY 16, 2023

A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. 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? The answer?

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

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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ETL Data Warehouse AWS Business Intelligence 52

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.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

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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ETL Data Warehouse Data Quality Data Governance 52

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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ETL Data Warehouse SQL Data Quality 52

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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ETL Azure AWS Data Governance 52

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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ETL SQL Data Warehouse Data Pipeline 52

Smart Data Collective

AUGUST 17, 2022

Kafka And ETL Processing: You might be using Apache Kafka for high-performance data pipelines, stream various analytics data, or run company critical assets using Kafka, but did you know that you can also use Kafka clusters to move data between multiple systems. Step 2: Create a Data Catalog table.

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Apache Kafka ETL Data Lakes AWS 130

Towards AI

MARCH 21, 2023

If you ever wonder how predictions and forecasts are made based on the raw data collected, stored, and processed in different formats by website feedback, customer surveys, and media analytics, this blog is for you. What are ETL and data pipelines? These data pipelines are built by data engineers.

Data Engineer 95

Data Engineer Data Engineering Data Engineering Data Engineering 95

IBM Data Science in Practice

NOVEMBER 28, 2022

As organizations steer their business strategies to become data-driven decision-making organizations, data and analytics are more crucial than ever before. The concept was first introduced back in 2016 but has gained more attention in the past few years as the amount of data has grown.

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Data Pipeline Data Quality Data Preparation Data Governance 130

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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ETL Data Quality Data Pipeline Data Warehouse 40

IBM Data Science in Practice

DECEMBER 7, 2022

One of the key elements that builds a data fabric architecture is to weave integrated data from many different sources, transform and enrich data, and deliver it to downstream data consumers. Studies have shown that 80% of time is spent on data preparation and cleansing, leaving only 20% of time for data analytics.

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Data Quality Data Pipeline Data Preparation ETL 130

Smart Data Collective

SEPTEMBER 19, 2022

billion on financial analytics by 2030. And Big Data is one such excellent opportunity ! Big Data is the collection and processing of huge volumes of different data types, which financial institutions use to gain insights into their business processes and make key company decisions. Improving Risk Assessment.

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Big Data Big Data Big Data Analytics Big Data Analytics 145

Dataconomy

JULY 29, 2024

Ed Posinitskii: Simplifying data workflows with DBT and Managed Airflow Following Mikhail, Ed Posinitskii discussed simplifying data workflows using DBT and Managed Airflow. He introduced Airflow as a robust tool for orchestrating data pipelines and DBT for data transformation within data warehouses.

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Apache Kafka Data Pipeline Data Warehouse ETL 91

IBM Journey to AI blog

OCTOBER 22, 2024

Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement. Indeed, IDC has predicted that by the end of 2024, 65% of CIOs will face pressure to adopt digital tech , such as generative AI and deep analytics.

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Data Silos Data Pipeline DataOps Business Intelligence 102

Data Science Blog

FEBRUARY 4, 2023

The machine sensor data can be monitored directly in real time via respective data pipelines (real-time stream analytics) or brought into an overall picture of aggregated key figures (reporting). material flow analysis) for manufacturing and supply chain.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

AWS Machine Learning Blog

MARCH 1, 2023

This post is co-written with Suhyoung Kim, General Manager at KakaoGames Data Analytics Lab. To solve this problem, we had to design a strong data pipeline to create the ML features from the raw data and MLOps. The ETL pipeline, MLOps pipeline, and ML inference should be rebuilt in a different AWS account.

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AWS ML ML ETL 102

Alation

MAY 16, 2023

A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. 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? The answer?

Data Pipeline 40

Data Pipeline Data Governance Data Lakes Data Warehouse 40

Women in Big Data

OCTOBER 9, 2024

These procedures are central to effective data management and crucial for deploying machine learning models and making data-driven decisions. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline?

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

Applied Data Science

AUGUST 2, 2021

Automation Automating data pipelines and models ➡️ 6. The Data Engineer Not everyone working on a data science project is a data scientist. Data engineers are the glue that binds the products of data scientists into a coherent and robust data pipeline.

Data Science 130

Data Science Data Scientist ML ML 130

AWS Machine Learning Blog

FEBRUARY 21, 2025

Previously, he was a Data & Machine Learning Engineer at AWS, where he worked closely with customers to develop enterprise-scale data infrastructure, including data lakes, analytics dashboards, and ETL pipelines. He specializes in designing, building, and optimizing large-scale data solutions.

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AWS Natural Language Processing Machine Learning Machine Learning 129

Precisely

FEBRUARY 20, 2025

If you cant use predictive analytics and make quick, confident data-driven decisions, you risk falling behind to your competitors that can. Solution: Ensure real-time insights and predictive analytics are both accurate and actionable with data integration.

Data Silos 68

Data Silos AI AI Data Quality 68

AWS Machine Learning Blog

JANUARY 7, 2025

The following are some steps to use TMX files for generative AI translations: TMX data pipeline TMX files contain structured translation units, but the format might need to be preprocessed to extract the source and target text segments in a format that can be consumed by the generative AI model.

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AWS Python AI AI 117

ODSC - Open Data Science

APRIL 23, 2025

Confluent Confluent provides a robust data streaming platform built around Apache Kafka. AI credits from Confluent can be used to implement real-time data pipelines, monitor data flows, and run stream-based ML applications. Modal Modal offers serverless compute tailored for data-intensive workloads.

Data Scientist 52

Data Scientist Azure Apache Kafka ML 52

phData

MAY 3, 2024

Leveraging real-time analytics to make informed decisions is the golden standard for virtually every business that collects data. If you have the Snowflake Data Cloud (or are considering migrating to Snowflake ), you’re a blog away from taking a step closer to real-time analytics.

Analytics 52

Analytics Analytics Apache Kafka ETL 52

phData

MARCH 8, 2023

With over 160 data connectors available, Fivetran makes it easy to move data out of, into, and across any cloud data platform in the market. It allows organizations to easily connect their disparate data sources without having to manage any infrastructure. Why Use Fivetran?

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Data Warehouse Data Engineering Data Engineer Data Engineering 96