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A Guide to Data Pipelines (And How to Design One From Scratch)

Striim

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

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Snowflake’s New Python API Empowers Data Engineers to Build Modern Data Pipelines with Ease

Snowflake

Since the previous Python connector API mostly communicated via SQL, it also hindered the ability to manage Snowflake objects natively in Python, restricting data pipeline efficiency and the ability to complete complex tasks. To get started, explore the comprehensive API documentation , which will guide you through every step.

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New Fivetran connector streamlines data workflows for real-time insights

ThoughtSpot

Those coveted insights live at the end of a process lovingly known as the data pipeline. The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users.

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Building Data Pipelines That Run From Source To Analysis And Activation With Hevo Data

Data Engineering Podcast

Building reliable data pipelines is a complex and costly undertaking with many layered requirements. In order to reduce the amount of time and effort required to build pipelines that power critical insights Manish Jethani co-founded Hevo Data. Data stacks are becoming more and more complex.

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4 Ways to Tackle Data Pipeline Optimization

Monte Carlo

Just as a watchmaker meticulously adjusts every tiny gear and spring in harmonious synchrony for flawless performance, modern data pipeline optimization requires a similar level of finesse and attention to detail. Learn how cost, processing speed, resilience, and data quality all contribute to effective data pipeline optimization.

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What Is Data Pipeline Automation?

Ascend.io

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

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What Is Data Pipeline Automation?

Ascend.io

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.