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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

Flipboard

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.

ETL 138
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Supercharging Your Data Pipeline with Apache Airflow (Part 2)

Heartbeat

Image Source —  Pixel Production Inc In the previous article, you were introduced to the intricacies of data pipelines, including the two major types of existing data pipelines. You might be curious how a simple tool like Apache Airflow can be powerful for managing complex data pipelines.

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. Let’s combine these suggestions to improve upon our original prompt: Human: Your job is to act as an expert on ETL pipelines.

Database 158
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Real‑time data streaming architecture: The essential guide to AI‑ready pipelines and instant personalization

Dataconomy

A 2025 landscape analysis shows ApacheKafka , Flink , and Iceberg moving from niche tools to fundamental parts of modern data architecture, underscoring how ubiquitous realtime expectations have become. Common pitfalls and how to avoid them Tomlein highlights five recurring traps: Data leakage Partition feature calcs strictly by event time.

AI 103
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Build trust in banking with data lineage

IBM Journey to AI blog

Before a bank can start the process of certifying a risk model, they first need to understand what data is being used and how it changes as it moves from a database to a model.

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Using Matillion Data Productivity Cloud to call APIs

phData

Matillion’s Data Productivity Cloud is a versatile platform designed to increase the productivity of data teams. It provides a unified platform for creating and managing data pipelines that are effective for both coders and non-coders. Each API has its own set of requirements.

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How Fifth Third Bank Implements a Data Mesh with Alation and Snowflake

Alation

You don’t have to write ETL jobs.” That lowers the barrier to entry because you don’t have to be an ETL developer. Data Pipeline Capabilities This team’s scope is massive because the data pipelines are huge and there are many different capabilities embedded in them. Invest in automation.