Challenge 1: Translate a GROUP BY Query — Possible Solution
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db.products.aggregate([
  { $group: {
      _id: "$category",
      product_count: { $sum: 1 },
      avg_price: { $avg: "$price" }
  } },
  { $sort: { product_count: -1 } }
])

WHY THIS WORKS AS AN ANSWER
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The SQL query has no WHERE clause, so the pipeline needs no $match
stage at all — every product participates in the grouping.

$group's _id holds the grouping key ("$category"), the same role
category plays after GROUP BY in the SQL version. COUNT(*) becomes
{ $sum: 1 } — adding 1 for every document in the group, since there's
no specific field being summed, just documents being counted. AVG(price)
becomes { $avg: "$price" } directly, MongoDB's accumulator mirroring
SQL's aggregate function almost exactly.

$sort then orders by product_count descending (-1), matching ORDER BY
product_count DESC. Note that $sort refers to product_count, the NEW
field name created by $group — not any field that existed on the
original product documents.