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Crafting a Data Pipeline: Navigating the Depths of Our ELT Architecture

Crafting a Data Pipeline: Navigating the Depths of Our ELT Architecture

Luthfir Rahman Bagaskara data engineering Freight-hub

Greetings tech enthusiasts! Join us on a journey through the intricate landscape of SaaS logistics, where data reigns supreme. In this blog, we’ll unravel the layers of sophistication within our ELT (Extract, Load, Transform) data pipeline—an orchestration meticulously composed using Python and BigQuery. Get ready for a nuanced exploration that’s reshaping the very fabric of data management in our dynamic industry.

We using Layering on our ELT Process from Database Production or another external sources to Google BigQuery, We have 4 Layers to tailoring our Table into one single source of data for our clients Report:

to individual client needs. It’s not just data transformation; it’s a symphony of tailored insights.

Layer 1 (L1): Extract and Load the Source(s)

Embark on the foundational notes of L1, where raw data emerges from production tables. No complexities, just extraction and loading the original table to our L1 Dataset.

Extract and Load the Source

Layer 2 (L2) and Layer 3(L3): Combining and Transforming

Enter the realm of L2, where tables gracefully intertwine based on functionality. Dimension tables emerge as artistic canvases, holding intricate details like user nuances and vehicle specifics. Beside them, Fact tables paint a vivid picture of our operations—orders, trips, finance, and beyond.

Discover the nuanced composition of L3, where data transforms to resonate with each client’s unique symphony. Business logic takes center stage, delicately crafted to cater to individual client needs. It’s not just data transformation; it’s a symphony of tailored insights.

Layer_combine_transforming

Layer 4 (L4): Harmonize the Data

The grand crescendo arrives in L4—the pinnacle of our orchestration. Here, L2 and client-specific L3 converge into a harmonious tableau. Picture a symphony of data accessibility, where multiple reports seamlessly emanate from this singular, data-rich source. It’s not merely a layer; it’s a crescendo, a culmination of orchestrated data brilliance. And last Product of our L4 use on some platforms and projects like Looker Studio, Auto Mailing, AI platform, and Machine Learning Project for advanced analytics

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Advantages Amplified:

  • Witness a significant reduction in data discrepancies as our approach prioritizes precision.
  • Precision in Data Notes

The Melody of Data Accessibility

  • L4 becomes the epicenter of a data symphony, simplifying the reporting process. Multiple reports effortlessly harmonize from this singular, powerhouse table.

Bespoke Transformations, Crafted like Art

  • The transformative power of L3 ensures that clients don’t just receive data; they experience a tailored masterpiece.

Conclusion:

Our ELT Pipeline transcends a mere pipeline; it’s a symphony of data orchestration. In the dynamic tapestry of SaaS logistics, this approach isn’t just about managing data; it’s a celebration of its essence. Join us in this tech-driven saga, where data isn’t just a commodity; it’s the hero of an eloquent tale.

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