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Data Pipeline vs. ETL: Which Delivers More Value?

Ascend.io

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. However, they are not just an upgraded version of ETL. Yet, the technical problem is the same.

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Data Engineering Weekly #127

Data Engineering Weekly

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make collecting data from every application, website, and SaaS platform easy, then activating it in your warehouse and business tools. Sign up free to test out the tool today.

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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

Machine Data: For IoT applications, sensor data extraction is used to collect information from devices, machinery, or sensors, enabling real-time monitoring and analysis. Customer Interaction Data: In customer-centric industries, extracting data from customer interactions (e.g.,

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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

As a result, a less senior team member was made responsible for modifying a production pipeline. Brooks law (for data): “ Adding data engineer personpower to a late data project makes it later.” Shouldn’t Marcus consider upgrading his technology? A better ETL tool? Pick some other hot tool?

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What is Azure Data Factory – Here’s Everything You Need to Know

Edureka

ADF connects to various data sources, including on-premises systems, cloud services, and SaaS applications. It then gathers and relocates information to a centralized hub in the cloud using the Copy Activity within data pipelines. Transform and Enhance the Data: Once centralized, data undergoes transformation and enrichment.

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Azure Synapse vs. Databricks – What Are the Differences?

Edureka

Key Advantages of Azure Synapse No Code AI or Analytics Capabilities Azure Synapse takes a significant leap forward in democratizing data analytics and AI by offering robust no-code options. Computational Muscle and Adaptability Tl;dr: The choice depends on your data processing requirements. Is Azure Synapse an ETL tool?