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Data News — Week 23.12

Christophe Blefari

Out of the box Mage provide all-in-one web editor to write data pipelines with a great UX. In small browser text areas you will be able to write Python, SQL or R code and orchestrate theses transformations with drag-n-drop. Kestra is a YAML-based data pipeline tool mixed with string templating.

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Handling Bursty Traffic in Real-Time Analytics Applications

Rockset

Both are extremely fast at the simple tasks they are designed for — retrieving individual values or whole documents — and that speed is largely unaffected by bursts of data. Database makers have experimented with different designs to scale for bursts of data traffic without sacrificing speed, features or cost.

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Data Pipeline Architecture: Understanding What Works Best for You

Ascend.io

Data pipelines are integral to business operations, regardless of whether they are meticulously built in-house or assembled using various tools. As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Ready to fortify your data management practice?

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Aggregator Leaf Tailer: An Alternative to Lambda Architecture for Real-Time Analytics

Rockset

That meant a system that was sufficiently nimble and powerful to execute fast SQL queries on raw data, essentially performing any needed transformations as part of the query step, and not as part of a complex data pipeline. Most processing in the Lambda architecture happens in the pipeline and not at query time.

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Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

Data Engineering Podcast

Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Data Lake 100
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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

. :) But before you start data engineering project ideas list, read the next section to know what your checklist for prepping for data engineering role should look like and why. Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer.

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Data Ingestion: 7 Challenges and 4 Best Practices

Monte Carlo

Other common transformations done within the ingestion phase are data formatting and deduplication. Data ingestion tools that automatically deploy connectors to collect and move data from source to target system without requiring Python coding skills can help relieve some of this pressure.