Analytics Academy

Learning Paths

Four paths to senior-level mastery

Assumes you already know SQL and data modeling. Tick modules off as you complete them — progress appears on your dashboard.

PATH A · Advanced · 64h

Advanced Microsoft Fabric

OneLake, Lakehouse vs Warehouse, Direct Lake and enterprise Power BI.

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Download starter repo — eaa-path-a-advanced-fabric (Spark notebooks)View on GitHub — smarteescloud/eaa-path-a-advanced-fabric
Setup guide — clone the repo and run the notebooks

1. Clone the starter repo:

git clone https://github.com/smarteescloud/eaa-path-a-advanced-fabric.git

2. In Microsoft Fabric: create a workspace with a capacity (or trial), then in the notebooks folder of the repo import each .ipynb as a Fabric notebook (Workspace → New → Notebook, or upload via OneLake / Git integration).

3. Attach a Spark runtime to the notebook, set the Lakehouse the notebook expects, and run cells top-to-bottom.

4. Cluster-free alternative: run the same notebooks in a Databricks workspace — the Spark code is portable.

Every notebook is self-contained: start at 01 and work downward. Progress on this page tracks the modules, not the notebooks.

PATH B · Advanced · 70h

Advanced Databricks

Delta internals, Spark performance, Unity Catalog and Lakeflow.

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Download starter repo — eaa-path-b-advanced-databricks (Spark notebooks)View on GitHub — smarteescloud/eaa-path-b-advanced-databricks
Setup guide — clone the repo and run the notebooks

1. Clone the starter repo:

git clone https://github.com/smarteescloud/eaa-path-b-advanced-databricks.git

2. In Databricks: Workspace → right-click a folder → Import, and upload the repo's notebooks (or connect the repo under Repos and browse it directly).

3. Attach an all-purpose cluster on a recent runtime (14.x+ recommended), then run cells in order.

4. No workspace? A free Community Edition account runs most of the exercises.

Every notebook is self-contained: start at 01 and work downward. Progress on this page tracks the modules, not the notebooks.

PATH C · Expert · 52h

Enterprise Analytics Architecture

Technology-independent modeling, governance and data product design.

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Download starter repo — eaa-path-c-enterprise-analytics-architecture (Spark notebooks)View on GitHub — smarteescloud/eaa-path-c-enterprise-analytics-architecture
Setup guide — clone the repo and run the notebooks

1. Clone the starter repo:

git clone https://github.com/smarteescloud/eaa-path-c-enterprise-analytics-architecture.git

2. The notebooks are platform-neutral: run them in any Spark 3.5+ environment — a Databricks Community Edition workspace or a Fabric trial capacity both work.

3. Import the notebooks, attach a cluster, and run cells in order.

Every notebook is self-contained: start at 01 and work downward. Progress on this page tracks the modules, not the notebooks.

PATH D · Expert · 28h

Cross-Platform Architecture

Decide confidently between Fabric and Databricks — and combine them.

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Download starter repo — eaa-path-d-cross-platform-architecture (Spark notebooks)View on GitHub — smarteescloud/eaa-path-d-cross-platform-architecture
Setup guide — clone the repo and run the notebooks

1. Clone the starter repo:

git clone https://github.com/smarteescloud/eaa-path-d-cross-platform-architecture.git

2. The notebooks are platform-neutral: run them in any Spark 3.5+ environment — a Databricks Community Edition workspace or a Fabric trial capacity both work.

3. Import the notebooks, attach a cluster, and run cells in order.

Every notebook is self-contained: start at 01 and work downward. Progress on this page tracks the modules, not the notebooks.