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PixelFed Analytics Engineering

Multi-format ingestion, dimensional modeling, and a version-controlled Power BI project.

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THE PROJECT / FOLLOW THE THREAD

A question. A process.
Work you can explore.

Follow the decisions behind the implementation, then inspect the original work.

01 / WHY THIS WORK EXISTS

The question behind the build.

Social-content data has different event grains, optional values, and timing constraints. Landing data also arrives in different file formats. Cleaning everything with the same rule can quietly change its meaning.

ProjectPixelFed Analytics Engineering
Available evidence8 linked files · visual preview
ExploreImplementation & documentation
02 / THE CHOICES & CONNECTIONS

Follow the implementation.

  1. 01

    Generate deterministic synthetic data against a documented schema contract.

  2. 02

    Separate natural optional nulls from deliberately injected raw-data quality issues.

  3. 03

    Validate a candidate landing refresh before explicit promotion and retain the prior snapshot.

  4. 04

    Use Power Query staging and conformed dimensions with grain-specific facts and documented relationships.

Power BIPythonSQLPostgreSQLMySQLDAXPower QueryExcel
Read the implementation notes
03 / OPEN THE WORK

See the work. Inspect the details.

The project makes the raw-to-Silver workflow reviewable: schemas, null-handling policies, validation, and manual Power Query guidance sit alongside the implementation.

Explore report preview & files Read the null-handling policy View the original source
04 / THE WORK BEHIND THE CLAIM

Choose where to look deeper.

Search the linked source inventory or narrow it to the kind of artifact you want to inspect. Files open at their original source.

8 linked source files

DOCREADME.mdDOCdocs/ingestion/raw-landing-to-silver-workflow.mdDOCCHANGELOG.mdDOCCODE_OF_CONDUCT.mdJSONconfig_table_format_assignment.jsonDOCCONTRIBUTING.mdDOCschema.mdPBIPPixelFed_report.pbip
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