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If your queries are slow… your data model might be the problem. Star Schema is the most widely used modeling technique in analytics. πŸ‘‰ One central fact table πŸ‘‰ Multiple dimension tables Result: βœ”
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Most data engineers know tools… But struggle with choosing the right data model. Here’s the truth: πŸ‘‰ Your data model decides performance, cost, and scalability Quick breakdown: β€’ Conceptual β†’ What
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Most people jump into tools like Spark, Snowflake, or Airflow… But the real game-changer? πŸ‘‰ Data Modeling It’s what separates: πŸ‘¨β€πŸ’» Coders vs System Designers Start thinking in: β€’ Fact vs Dimens
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How ontology replaces traditional data modeling In traditional data warehouses, we model data using tables, keys, and joins. But in Palantir Foundry, ontology models real-world entities and relation
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Why ontology is more powerful than a data warehouse Traditional data warehouses focus on storing and querying data. But in Palantir Foundry, ontology maps data into real-world entities and relations
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Spark Profiles in Foundry Code Repositories When building ETL pipelines in Palantir Foundry, Spark profiles control how transforms execute on Spark clusters. They configure: β€’ executor memory β€’ clu
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Code Repositories for ETL Pipelines In Palantir Foundry, ETL transformations are often written in code repositories using SQL or PySpark. These repositories store the logic that powers data pipeline
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Code Repositories in Foundry In Palantir Foundry, engineers use code repositories to build reusable Python logic and APIs. Using decorators, Python functions can be exposed as Foundry functions that
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Connecting Databricks with Foundry To ingest data from Databricks into Palantir Foundry, engineers create a data connection that syncs tables into raw datasets. Typical flow: Databricks β†’ Data Conn
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AI agents don’t just need models. They need memory architectures. From RAG pipelines to long-term memory and multi-agent shared memory, modern AI systems rely on retrieval patterns that transform sto
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AI agents don’t just need models. They need memory architectures. From RAG pipelines to long-term memory and multi-agent shared memory, modern AI systems rely on retrieval patterns that transform sto
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Data Connections in Foundry Before building pipelines in Palantir Foundry, data must first enter the platform. Data Connections allow engineers to ingest data from: β€’ databases β€’ APIs β€’ files β€’ str
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About @dataengnotebook

Data Engineering Notebook is a Instagram growing creator. With 43 followers and 103 posts, dataengnotebook's account shows a follower-to-following ratio of 2.3:1. View all content anonymously on Pictame - no login required.

dataengnotebook's engagement rate sits at 6.98%. That's 40% above what you'd typically see for accounts with 1K-10K followers (average 5%) β€” a sign of a genuinely connected audience.

Out of the last 12 posts, 92% are videos and 8% are photos. Notably, videos tend to get 1.5x more engagement than photos. New posts appear roughly every 2 days β€” a steady, reliable rhythm. Captions lean moderate, averaging 436 characters.

6.98% engagement rate β€” 40% above average for 1K-10K follower accounts.
92% videos, 8% photos. Videos get 1.5x more engagement here.
New content every 2 days β€” a steady rhythm.
2.3:1 follower-to-following ratio.

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Data Engineering Notebook

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Data Engineering in simple words. Cloud β€’ ETL β€’ Lakehouse Daily notes from the notebook.

medium.com/@satyamkumar339
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