DataLane

Problem tracks

SQL warehouse sets and Python (NumPy / PyTorch) sets. Filter by the role you are practicing for.

SQL · Track 1 · 5 problems

SQL Foundations

The eight-minute questions that open a screen: filtered aggregation, product joins, and the org-tree self-join.

0/5

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Data Analyst · BI Analyst · Analytics Engineer · Data Engineer · Data Scientist

SQL · Track 2 · 4 problems

Warehouse SQL Core

The everyday warehouse screen: anti-joins, rates, daily grain, and a customer dimension that survives LEFT JOIN.

0/4

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Analytics Engineer · Data Engineer · BI Analyst · Data Analyst · Data Architect

SQL · Track 3 · 4 problems

Windows & Time Series

Running totals, trailing averages, growth, and share of total — every question here turns on the frame.

0/4

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Data Engineer · Analytics Engineer · Data Scientist · Data Analyst

SQL · Track 4 · 3 problems

Ranking & Dedup

Latest row per key, top-N per group, and the department-average trap. ROW_NUMBER earns its keep here.

0/3

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Data Engineer · Analytics Engineer · BI Analyst · Data Scientist

SQL · Track 5 · 11 problems

Data Quality & Hard SQL

Reconciliation, JSON payloads, pivots, median without percentiles, and sessionization. The back half of the loop.

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Data Engineer · ML Engineer · MLOps Engineer · AI Engineer · Data Architect

Python · Track 6 · 6 problems

Python Foundations

The pad that opens an analyst or DE screen: means, activations, clip, flatten. Same tests in NumPy, Python, and PyTorch.

0/6

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Data Analyst · Data Engineer · Analytics Engineer · Data Scientist · Data Architect

Python · Track 7 · 7 problems

Stats the analyst pad asks

NaN-aware means, variance, median, z-score, and a weighted KPI. Spreadsheet instincts, code you can defend.

0/7

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Data Analyst · BI Analyst · Analytics Engineer · Data Engineer

Python · Track 8 · 7 problems

ML metrics

Losses and scores a scientist or ML engineer must implement without sklearn: MSE, R², precision, recall, F1, BCE.

0/7

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Data Scientist · ML Engineer · MLOps Engineer · AI Engineer

Python · Track 9 · 8 problems

Tensors & ranking

Softmax, log-softmax, cosine, top-k, KL, Huber — the DS/MLE follow-up after the metric pad.

0/8

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Data Scientist · ML Engineer · MLOps Engineer · AI Engineer

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