diff --git a/AI_ASSIST.md b/AI_ASSIST.md
index b134b96..2b3a68b 100644
--- a/AI_ASSIST.md
+++ b/AI_ASSIST.md
@@ -1,16 +1,19 @@
-# AI Usage Log
+# AI assistance log
 
-Record at least one point where you used an AI coding assistant (ChatGPT, Claude, Cursor, GitHub Copilot, Gemini, etc.) during this assignment.
+## Where I used an LLM
 
-## Interaction 1
+I used ChatGPT while debugging the local dbt-to-Databricks setup and while
+organising the assignment repository. The main issues discussed were:
 
-- **Tool used:** (e.g. ChatGPT / Cursor / Claude)
-- **Task / Problem:** (e.g. debugging dbt connection profile / writing PySpark join / configuring Job trigger)
-- **Prompt sent:**
-  > `___`
-- **Output provided by AI:**
-  > `___`
-- **What I kept, changed, or rejected, and why:**
-  > `___`
+- the Databricks adapter and `dbt_utils` package were missing;
+- Git Bash converted `/sql/1.0/warehouses/...` into a Windows path;
+- the source schema was incorrectly set to `public` instead of `nyc_yellow`;
+- dbt initially authenticated with another user's token;
+- the assignment repository contained only empty placeholder files.
 
-*(Ensure no personal passwords, Databricks tokens, or unapproved credentials are included in prompts or logged outputs.)*
+## How I checked the advice
+
+I did not accept the suggestions blindly. I checked them with `dbt --version`,
+`dbt deps`, `dbt debug`, `session_user()`, compiled SQL, and the Databricks error
+messages. I also kept all real tokens outside Git and left real timings,
+Job URLs, and screenshots as manual evidence rather than inventing results.
diff --git a/README.md b/README.md
index fd4900b..c527b82 100644
--- a/README.md
+++ b/README.md
@@ -1,74 +1,105 @@
-# HackYourFuture Data Track — Week 13 Assignment
+# Week 13 Assignment — Big Data on Databricks
 
-**Databricks Lab:** PySpark exploration, dbt incremental models on Delta Lake, and Git-backed Job scheduling.
+This repository contains Halyna's Week 13 assignment scaffold for:
 
-Full instructions live in the curriculum: [Week 13 Assignment](https://www.notion.so/hackyourfuture/Assignment-2af50f64ffc98112b371c42a3f469749).
+1. PySpark exploration in a Databricks notebook.
+2. A Week 10 dbt project ported to Databricks and Delta Lake.
+3. A Git-backed Databricks Job with a paused schedule.
 
-## Where to start
+The complete Ukrainian translation of the assignment is in [`ASSIGNMENT_UA.md`](ASSIGNMENT_UA.md).
+A file-by-file explanation is in [`CHANGES_UA.md`](CHANGES_UA.md).
 
-| Folder / File | What to submit | Points (autograder) |
-| --- | --- | --- |
-| `task-1/` | PySpark notebook (`show()` on aggregated results, PySpark-vs-dbt note) | 25 |
-| `task-2/` | Ported dbt project + `WRITEUP.md` (timings + incremental explanation + `DESCRIBE HISTORY`) | 30 |
-| `task-3/` | Git-backed Databricks Job + screenshots + `SCHEDULING.md` (Jobs vs Airflow) | 15 |
-| `AI_ASSIST.md` | Documented LLM usage (prompt, tool, kept/discarded rationale) | 15 |
-| Required files | Presence of all required files across `task-1/`, `task-2/`, `task-3/`, and `AI_ASSIST.md` | 15 |
-| Secrets hygiene | No committed secrets (`profiles.yml`, `.env`, tokens) | Blocker if violated |
-
-**Passing score:** 60/100 on the autograder. Your teacher also reviews quality against the rubric (incremental config, `>` boundary, tool-choice writing, Job configuration).
-
-## Repository layout
+## Repository structure
 
 ```text
-data-assignment-week-13/
+c55-data-week-13/
 ├── task-1/
-│   └── pyspark_exploration.ipynb    # or .py export from Databricks
+│   └── pyspark_exploration.py
 ├── task-2/
-│   ├── dbt_project.yml              # your ported Week 10 project
-│   ├── models/                      # your dbt models
+│   ├── dbt_project.yml
+│   ├── packages.yml
 │   ├── profiles.yml.example
-│   └── WRITEUP.md                   # incremental build write-up + DESCRIBE HISTORY
-├── task-3/                          # Git-backed Job scheduling
-│   ├── SCHEDULING.md                # Jobs vs Airflow write-up + Job Run URL
-│   └── screenshots/                 # Job config, green run, paused trigger
-├── task-4/                          # optional bonuses only (create if needed)
+│   ├── pyproject.toml
+│   ├── models/
+│   ├── tests/
+│   └── WRITEUP.md
+├── task-3/
+│   ├── SCHEDULING.md
+│   └── screenshots/
 ├── .env.example
-├── AI_ASSIST.md                     # LLM interaction log
-└── README.md
+├── AI_ASSIST.md
+└── ASSIGNMENT_UA.md
 ```
 
-## Setup
+## What still requires manual evidence
+
+The code and templates are prepared, but these values cannot be invented and must be added after real Databricks runs:
+
+- the output of Task 1;
+- the full-refresh and incremental wall-clock times;
+- the `DESCRIBE HISTORY` result or screenshot;
+- the Databricks Job Run URL;
+- screenshots of Job configuration, a successful run, and the paused schedule.
+
+## Local dbt setup
+
+Run these commands from `task-2/`:
 
 ```bash
-cp .env.example .env          # fill in Databricks connection values
-cd task-2
 cp profiles.yml.example profiles.yml
-export $(grep -v '^#' ../.env | xargs)   # or source manually
-dbt debug
+cp ../.env.example ../.env
+```
+
+Fill in `../.env` with your personal token and correct warehouse values, then load it in Git Bash:
+
+```bash
+set -a
+source ../.env
+set +a
+```
+
+Git Bash can convert `/sql/...` into a Windows path. Prevent that before running dbt:
+
+```bash
+export MSYS2_ENV_CONV_EXCL='DATABRICKS_HTTP_PATH'
 ```
 
-Use Python 3.11 or 3.12 for dbt if `dbt debug` crashes on import (`uvx --python 3.11 --from dbt-databricks dbt debug`).
+Install and check dbt:
+
+```bash
+uv sync
+uv run dbt deps
+uv run dbt debug
+```
 
-## Check your score locally
+First create the staging views once:
 
 ```bash
-bash .hyf/test.sh
-cat .hyf/score.json
+uv run dbt run --select +fct_trips
 ```
 
-## Scoring ladder (autograder)
+Then run the two commands required for the timing comparison:
 
-| Score | What the grader checks |
-| --- | --- |
-| 15 | Required files present (`task-1` notebook, `task-2/dbt_project.yml`, `WRITEUP.md`, `SCHEDULING.md`, `AI_ASSIST.md`) |
-| 25 | Task 1 notebook mentions `show` and borough/payment_type work |
-| 30 | Task 2 has incremental config (`materialized='incremental'`, `merge`, `unique_key`) and a filled `WRITEUP.md` |
-| 15 | Task 3 has screenshots in `task-3/screenshots/`, Job Run URL, and a filled `SCHEDULING.md` |
-| 15 | `AI_ASSIST.md` contains documented prompt and rationale |
-| Pass | Secrets hygiene (no committed `.env` / `profiles.yml` / `dapi` tokens) |
+```bash
+uv run dbt build --select fct_trips --full-refresh
+uv run dbt build --select fct_trips
+```
+
+## Databricks Job configuration
 
-Governance and streaming bonuses are teacher-reviewed only; they do not affect the autograder score.
+Use these values:
 
-## Instructor / track maintainer
+```text
+Job name: dev_halyna_fct_trips
+Git repository: https://github.com/halyna1995/c55-data-week-13.git
+Branch: main
+Project directory: task-2
+Commands:
+  dbt deps
+  dbt build --select fct_trips
+Warehouse: hyf-dbt-warehouse
+Catalog: hyf
+Schema: dev_halyna
+```
 
-This repo is the Week 13 student scaffold. Teacher rubric: `week_13__assignment_rubric.md` in the [datatrack](https://github.com/HackYourFuture/datatrack) curriculum repo (not shared with students).
+After proving the Job works, add a schedule and leave the trigger **Paused**.
diff --git a/task-1/screenshots/task1_pyspark_code.png b/task-1/screenshots/task1_pyspark_code.png
new file mode 100644
index 0000000..1d1b00e
Binary files /dev/null and b/task-1/screenshots/task1_pyspark_code.png differ
diff --git a/task-1/screenshots/task1_pyspark_results.png b/task-1/screenshots/task1_pyspark_results.png
new file mode 100644
index 0000000..b5783b3
Binary files /dev/null and b/task-1/screenshots/task1_pyspark_results.png differ
diff --git a/task-1/task-1-week-13-halyna.py b/task-1/task-1-week-13-halyna.py
new file mode 100644
index 0000000..bf99a69
--- /dev/null
+++ b/task-1/task-1-week-13-halyna.py
@@ -0,0 +1,48 @@
+# Databricks notebook source
+from pyspark.sql import functions as F
+
+trips = spark.read.table("hyf.nyc_yellow.raw_trips")
+zones = spark.read.table("hyf.nyc_yellow.raw_zones").select(
+    "location_id",
+    "borough",
+)
+
+
+# Question 1: Which pickup borough has the most trips?
+pickup_counts = (
+    trips
+    .join(
+        F.broadcast(zones),
+        trips.pickup_location_id == zones.location_id,
+        "left",
+    )
+    .groupBy("borough")
+    .agg(F.count("*").alias("trip_count"))
+)
+
+top_pickup_borough = (
+    pickup_counts
+    .orderBy(F.desc("trip_count"))
+    .limit(1)
+    .select(
+        F.lit("Pickup borough with most trips").alias("metric"),
+        F.coalesce(F.col("borough"), F.lit("Unknown")).alias("category"),
+        F.col("trip_count").cast("double").alias("value"),
+    )
+)
+
+# Question 2: What is the average total_amount per payment_type?
+average_total_by_payment = (
+    trips
+    .groupBy("payment_type")
+    .agg(F.avg("total_amount").alias("avg_total_amount"))
+    .select(
+        F.lit("Average total_amount by payment_type").alias("metric"),
+        F.col("payment_type").cast("string").alias("category"),
+        F.round("avg_total_amount", 2).cast("double").alias("value"),
+    )
+)
+
+# One final action for both answers.
+results = top_pickup_borough.unionByName(average_total_by_payment)
+results.orderBy("metric", "category").show(truncate=False)
diff --git a/task-2/README.md b/task-2/README.md
index a68eced..748cb5d 100644
--- a/task-2/README.md
+++ b/task-2/README.md
@@ -1,12 +1,53 @@
-# Task 2: dbt on Databricks
+# Task 2 — dbt on Databricks
 
-Copy your **Week 10 dbt project** into this folder (or start from the `week-13-ch-4-dbt` branch of [nyc-taxi-dbt-reference](https://github.com/lassebenni/nyc-taxi-dbt-reference)).
+## 1. Create local secret files
 
-**Required changes:**
+```bash
+cp profiles.yml.example profiles.yml
+cp ../.env.example ../.env
+```
 
-1. Install `dbt-databricks` locally (`pip install dbt-databricks` or `uv tool install dbt-databricks`).
-2. Copy `profiles.yml.example` to `profiles.yml` (git-ignored) and export the env vars from `.env.example`.
-3. Configure `fct_trips` as `materialized='incremental'` with `incremental_strategy='merge'` and a real `unique_key`.
-4. Run `dbt build --select fct_trips --full-refresh` for the baseline, then `dbt build --select fct_trips` for the incremental rerun. Document both timings plus your explanation in `WRITEUP.md`.
+Fill `../.env` with your own values. Never commit `.env`, `profiles.yml`, or a token.
 
-**Do not commit:** `profiles.yml`, `.env`, or any Databricks token.
+## 2. Load the environment in Git Bash
+
+```bash
+export MSYS2_ENV_CONV_EXCL='DATABRICKS_HTTP_PATH'
+set -a
+source ../.env
+set +a
+```
+
+## 3. Install and verify
+
+```bash
+uv sync
+uv run dbt deps
+uv run dbt debug
+uv run dbt show --inline "select session_user() as dbt_identity"
+```
+
+The identity must be your own Databricks user, not the teacher's account.
+
+## 4. Create dependencies once
+
+```bash
+uv run dbt run --select +fct_trips
+```
+
+## 5. Required timed runs
+
+```bash
+uv run dbt build --select fct_trips --full-refresh
+uv run dbt build --select fct_trips
+```
+
+Copy the real times to `WRITEUP.md`.
+
+## 6. Verify Delta history
+
+```sql
+DESCRIBE HISTORY hyf.dev_halyna.fct_trips;
+```
+
+Save the result or screenshot and reference it in `WRITEUP.md`.
diff --git a/task-2/WRITEUP.md b/task-2/WRITEUP.md
index f3d1eb3..6b6b7d3 100644
--- a/task-2/WRITEUP.md
+++ b/task-2/WRITEUP.md
@@ -1,24 +1,47 @@
-# Task 2 write-up: incremental build timings & Delta history
+# Task 2 — dbt on Databricks and incremental models
 
-Fill in after running `dbt build --select fct_trips --full-refresh` baseline followed by `dbt build --select fct_trips` incremental rerun against Databricks.
+## Connection check
 
-## First build (full / initial load with --full-refresh)
+- Target catalog: `hyf`
+- Target schema: `dev_halyna`
+- SQL warehouse: `hyf-dbt-warehouse`
+- `dbt debug`: PASS
 
-- **Wall-clock time:**
-- **Notes:** (optional: warehouse size, any errors you fixed)
+## Build timings
 
-## Second build (incremental rerun)
+| Run | Command | Real wall-clock time |
+|---|---|---:|
+| Initial full build | `dbt build --select fct_trips --full-refresh` | 2m8.436s |
+| Incremental rerun | `dbt build --select fct_trips` | 1m54.189s |
 
-- **Wall-clock time:**
+The incremental rerun was modestly faster because `is_incremental()` returned
+true after the target Delta table already existed. The filter using `{{ this }}`
+read the maximum existing `pickup_datetime` from the current `fct_trips` table
+and processed only rows with a strictly newer timestamp instead of rebuilding
+the complete trip history.
 
-## Why was the second run faster?
+The incremental boundary uses `>` rather than `>=`. This prevents rows at the
+existing maximum timestamp from being processed repeatedly and avoids duplicate
+boundary records.
 
-Write two or three sentences in your own words (see the assignment for the concepts you must name):
+The measured difference was relatively small because the total wall-clock time
+also includes dbt startup, SQL warehouse execution, Delta `MERGE`, and data
+tests. However, the Delta table history confirms that the second run used the
+incremental `MERGE` strategy rather than performing another full table rebuild.
 
-`___`
+## Delta history proof
 
-## Delta Table History (DESCRIBE HISTORY)
+ The following command was executed in Databricks SQL Editor:
 
-Paste the output or summary of `DESCRIBE HISTORY hyf.dev_yourname.fct_trips` (showing `CREATE OR REPLACE TABLE` and `MERGE` operations) or reference a screenshot:
+```sql
+DESCRIBE HISTORY hyf.dev_halyna.fct_trips;
+```
 
-`___`
+The Delta history shows:
+
+CREATE OR REPLACE TABLE AS SELECT for the full-refresh builds;
+MERGE for the incremental reruns.
+
+Evidence:
+
+- Suggested screenshot path: `screenshots/delta_history.png`.
diff --git a/task-2/dbt_project.yml b/task-2/dbt_project.yml
new file mode 100644
index 0000000..198d9c9
--- /dev/null
+++ b/task-2/dbt_project.yml
@@ -0,0 +1,22 @@
+name: "nyc_taxi"
+version: "1.0.0"
+config-version: 2
+profile: "nyc_taxi"
+
+model-paths: ["models"]
+test-paths: ["tests"]
+macro-paths: ["macros"]
+seed-paths: ["seeds"]
+snapshot-paths: ["snapshots"]
+analysis-paths: ["analyses"]
+
+clean-targets:
+  - "target"
+  - "dbt_packages"
+
+models:
+  nyc_taxi:
+    staging:
+      +materialized: view
+    marts:
+      +materialized: table
diff --git a/task-2/models/marts/_fct_trips.yml b/task-2/models/marts/_fct_trips.yml
new file mode 100644
index 0000000..41e29b5
--- /dev/null
+++ b/task-2/models/marts/_fct_trips.yml
@@ -0,0 +1,19 @@
+version: 2
+
+models:
+  - name: fct_trips
+    description: Incremental NYC yellow taxi mart enriched with pickup and dropoff zones.
+    columns:
+      - name: trip_id
+        description: Surrogate key used by the Delta merge strategy.
+        data_tests:
+          - not_null
+          - unique
+      - name: pickup_datetime
+        description: Time when the trip started.
+        data_tests:
+          - not_null
+      - name: pickup_borough
+        description: Borough of the pickup zone.
+      - name: dropoff_borough
+        description: Borough of the dropoff zone.
diff --git a/task-2/models/marts/fct_trips.sql b/task-2/models/marts/fct_trips.sql
new file mode 100644
index 0000000..5adeb22
--- /dev/null
+++ b/task-2/models/marts/fct_trips.sql
@@ -0,0 +1,36 @@
+{{
+  config(
+    materialized='incremental',
+    incremental_strategy='merge',
+    unique_key='trip_id'
+  )
+}}
+
+select
+    t.trip_id,
+    t.pickup_datetime,
+    t.dropoff_datetime,
+    t.fare_amount,
+    t.tip_amount,
+    t.trip_distance,
+    t.total_amount,
+    t.trip_duration_minutes,
+    t.tip_pct,
+    t.fare_per_mile,
+    t.payment_type_label,
+    pz.borough as pickup_borough,
+    pz.zone as pickup_zone,
+    dz.borough as dropoff_borough,
+    dz.zone as dropoff_zone
+from {{ ref('stg_trips') }} t
+left join {{ ref('stg_zones') }} pz
+    on t.pickup_location_id = pz.location_id
+left join {{ ref('stg_zones') }} dz
+    on t.dropoff_location_id = dz.location_id
+
+{% if is_incremental() %}
+    where t.pickup_datetime > (
+        select max(pickup_datetime)
+        from {{ this }}
+    )
+{% endif %}
diff --git a/task-2/models/staging/_sources.yml b/task-2/models/staging/_sources.yml
new file mode 100644
index 0000000..2eb23ab
--- /dev/null
+++ b/task-2/models/staging/_sources.yml
@@ -0,0 +1,12 @@
+version: 2
+
+sources:
+  - name: nyc_taxi
+    description: Raw NYC yellow taxi data in Databricks Unity Catalog.
+    database: hyf
+    schema: nyc_yellow
+    tables:
+      - name: raw_trips
+        description: Yellow taxi trips for 2023-2025, approximately 128 million rows.
+      - name: raw_zones
+        description: Lookup table mapping taxi location IDs to boroughs and zones.
diff --git a/task-2/models/staging/_stg_trips.yml b/task-2/models/staging/_stg_trips.yml
new file mode 100644
index 0000000..42e33b7
--- /dev/null
+++ b/task-2/models/staging/_stg_trips.yml
@@ -0,0 +1,47 @@
+version: 2
+
+models:
+  - name: stg_trips
+    description: Cleaned yellow taxi trips with one row per generated trip_id.
+    data_tests:
+      - dbt_utils.unique_combination_of_columns:
+          arguments:
+            combination_of_columns:
+              - pickup_datetime
+              - dropoff_datetime
+              - pickup_location_id
+              - fare_amount
+          config:
+            severity: warn
+    columns:
+      - name: trip_id
+        description: Surrogate key generated from stable trip fields.
+        data_tests:
+          - not_null
+          - unique
+
+      - name: pickup_datetime
+        description: Time when the trip started.
+        data_tests:
+          - not_null
+
+      - name: pickup_location_id
+        description: TLC zone ID where the trip started.
+        data_tests:
+          - not_null
+          - relationships:
+              arguments:
+                to: ref('stg_zones')
+                field: location_id
+              config:
+                severity: warn
+
+      - name: payment_type
+        description: TLC payment code. The large dataset also contains code 0.
+        data_tests:
+          - not_null:
+              config:
+                severity: warn
+          - accepted_values:
+              arguments:
+                values: [0, 1, 2, 3, 4, 5, 6]
diff --git a/task-2/models/staging/_stg_zones.yml b/task-2/models/staging/_stg_zones.yml
new file mode 100644
index 0000000..47156ad
--- /dev/null
+++ b/task-2/models/staging/_stg_zones.yml
@@ -0,0 +1,13 @@
+version: 2
+
+models:
+  - name: stg_zones
+    description: One row per TLC taxi zone.
+    columns:
+      - name: location_id
+        description: TLC taxi-zone identifier.
+        data_tests:
+          - unique
+          - not_null
+      - name: borough
+        description: NYC borough name.
diff --git a/task-2/models/staging/stg_trips.sql b/task-2/models/staging/stg_trips.sql
new file mode 100644
index 0000000..908d302
--- /dev/null
+++ b/task-2/models/staging/stg_trips.sql
@@ -0,0 +1,63 @@
+{{ config(materialized='view') }}
+
+{% set payment_types = {
+    0: 'Flex Fare / unknown',
+    1: 'Credit card',
+    2: 'Cash',
+    3: 'No charge',
+    4: 'Dispute',
+    5: 'Unknown',
+    6: 'Voided trip'
+} %}
+
+with base as (
+    select
+        {{ dbt_utils.generate_surrogate_key([
+            'vendor_id',
+            'pickup_datetime',
+            'dropoff_datetime',
+            'pickup_location_id',
+            'dropoff_location_id',
+            'fare_amount',
+            'trip_distance',
+            'total_amount',
+            'passenger_count'
+        ]) }} as trip_id,
+        pickup_datetime,
+        dropoff_datetime,
+        pickup_location_id,
+        dropoff_location_id,
+        fare_amount,
+        tip_amount,
+        trip_distance,
+        total_amount,
+        payment_type,
+        case
+            when fare_amount > 0 then round(tip_amount / fare_amount, 4)
+            else null
+        end as tip_pct,
+        case
+            when trip_distance > 0 then round(fare_amount / trip_distance, 4)
+            else null
+        end as fare_per_mile,
+        case payment_type
+            {% for code, label in payment_types.items() %}
+            when {{ code }} then '{{ label }}'
+            {% endfor %}
+            else 'Other'
+        end as payment_type_label,
+        round(
+            (unix_timestamp(dropoff_datetime) - unix_timestamp(pickup_datetime)) / 60.0,
+            2
+        ) as trip_duration_minutes
+    from {{ source('nyc_taxi', 'raw_trips') }}
+    where pickup_location_id is not null
+      and fare_amount >= 0
+)
+
+select *
+from base
+qualify row_number() over (
+    partition by trip_id
+    order by pickup_datetime
+) = 1
diff --git a/task-2/models/staging/stg_zones.sql b/task-2/models/staging/stg_zones.sql
new file mode 100644
index 0000000..1e98897
--- /dev/null
+++ b/task-2/models/staging/stg_zones.sql
@@ -0,0 +1,6 @@
+select
+    location_id,
+    borough,
+    zone,
+    service_zone
+from {{ source('nyc_taxi', 'raw_zones') }}
diff --git a/task-2/package-lock.yml b/task-2/package-lock.yml
new file mode 100644
index 0000000..f683b32
--- /dev/null
+++ b/task-2/package-lock.yml
@@ -0,0 +1,5 @@
+packages:
+  - name: dbt_utils
+    package: dbt-labs/dbt_utils
+    version: 1.4.1
+sha1_hash: e6424ba9e5a22487e47f023803aa4f0411946808
diff --git a/task-2/packages.yml b/task-2/packages.yml
new file mode 100644
index 0000000..b26b1ff
--- /dev/null
+++ b/task-2/packages.yml
@@ -0,0 +1,3 @@
+packages:
+  - package: dbt-labs/dbt_utils
+    version: [">=1.1.0", "<2.0.0"]
diff --git a/task-2/pyproject.toml b/task-2/pyproject.toml
new file mode 100644
index 0000000..2892a22
--- /dev/null
+++ b/task-2/pyproject.toml
@@ -0,0 +1,8 @@
+[project]
+name = "week-13-dbt-databricks"
+version = "0.1.0"
+description = "HYF Week 13 dbt project for Databricks"
+requires-python = ">=3.11,<3.14"
+dependencies = [
+    "dbt-databricks>=1.10,<1.11",
+]
diff --git a/task-2/screenshots/delta_history.png b/task-2/screenshots/delta_history.png
new file mode 100644
index 0000000..279ddee
Binary files /dev/null and b/task-2/screenshots/delta_history.png differ
diff --git a/task-2/tests/assert_fare_amount_non_negative.sql b/task-2/tests/assert_fare_amount_non_negative.sql
new file mode 100644
index 0000000..0b6fbe5
--- /dev/null
+++ b/task-2/tests/assert_fare_amount_non_negative.sql
@@ -0,0 +1,5 @@
+select
+    pickup_datetime,
+    fare_amount
+from {{ ref('stg_trips') }}
+where fare_amount < 0
diff --git a/task-2/tests/assert_pickup_before_dropoff.sql b/task-2/tests/assert_pickup_before_dropoff.sql
new file mode 100644
index 0000000..8ebb206
--- /dev/null
+++ b/task-2/tests/assert_pickup_before_dropoff.sql
@@ -0,0 +1,8 @@
+{{ config(severity='warn') }}
+
+select
+    pickup_datetime,
+    dropoff_datetime,
+    pickup_location_id
+from {{ ref('stg_trips') }}
+where pickup_datetime > dropoff_datetime
diff --git a/task-3/SCHEDULING.md b/task-3/SCHEDULING.md
index 2780686..26b6f7f 100644
--- a/task-3/SCHEDULING.md
+++ b/task-3/SCHEDULING.md
@@ -1,23 +1,47 @@
-# Task 3 Write-up: Git-backed Job Scheduling
+# Task 3 — Git-backed Databricks Job
 
-## Databricks Job Run URL
+## Job configuration
 
-Paste the URL of your successful Job run from the Databricks UI address bar:
+- Job name: `dev_halyna_fct_trips`
+- Task name: `dbt_fct_trips`
+- Source: Git provider
+- Repository: `https://github.com/halyna1995/c55-data-week-13.git`
+- Branch: `main`
+- Project directory: `task-2`
+- SQL warehouse: `hyf-dbt-warehouse`
+- Catalog: `hyf`
+- Schema: `dev_halyna`
+- Commands:
 
-`___`
+```text
+dbt deps
+dbt build --select fct_trips
+```
 
-## Screenshots
+## Job Run URL
 
-Ensure the following screenshot files exist in `task-3/screenshots/`:
+https://adb-7405619530719547.7.azuredatabricks.net/jobs/872113922216601?o=7405619530719547
 
-1. `job_config.png` — Showing the dbt task configuration with Git repository URL, branch `main`, path `task-2`, and warehouse `hyf-dbt-warehouse`.
-2. `job_run_success.png` — Showing a successful run log with a green checkmark and stdout execution output.
-3. `job_schedule_paused.png` — Showing the scheduled trigger set to **Paused**.
+The Job completed successfully. The incremental fct_trips model was created,
+and all three dbt data tests passed. The final output showed:
+PASS=4 WARN=0 ERROR=0 SKIP=0 NO-OP=0 TOTAL=4
 
-## Orchestration Comparison
+## Required screenshots
 
-### When would you choose Databricks Jobs versus Apache Airflow for pipeline orchestration?
+- [ ] [`screenshots/job_config.png`](screenshots/job_config.png)
+- [ ] [`screenshots/job_success.png`](screenshots/job_success.png)
+- [ ] [`screenshots/paused_schedule.png`](screenshots/paused_schedule.png)
 
-Write two to three sentences comparing Databricks Jobs and Apache Airflow in your own words:
 
-`___`
+## Databricks Jobs versus Airflow
+
+I would use a Databricks Job when the workflow is Databricks-native, for example
+a dbt task, SQL task, or notebook that reads and writes Unity Catalog tables.
+I would use Airflow when one pipeline must coordinate several external systems,
+for example an API, Azure Storage, Postgres, Databricks, and notifications.
+
+## Schedule safety
+
+A daily schedule was added and immediately paused. This demonstrates that the
+Job can run automatically while preventing unnecessary use of the shared class
+compute budget.
diff --git a/task-3/screenshots/README.md b/task-3/screenshots/README.md
new file mode 100644
index 0000000..b8c13a3
--- /dev/null
+++ b/task-3/screenshots/README.md
@@ -0,0 +1,8 @@
+# Required Job screenshots
+
+Save the real images with exactly these names:
+
+1. `job_task_configuration.png` — Git URL, branch, `task-2` project directory,
+   dbt commands, warehouse, catalog, and schema.
+2. `job_successful_run.png` — green run and dbt output.
+3. `job_paused_schedule.png` — schedule visible with status Paused.
diff --git a/task-3/screenshots/job_config.png b/task-3/screenshots/job_config.png
new file mode 100644
index 0000000..75a2c98
Binary files /dev/null and b/task-3/screenshots/job_config.png differ
diff --git a/task-3/screenshots/job_success.png b/task-3/screenshots/job_success.png
new file mode 100644
index 0000000..d13216e
Binary files /dev/null and b/task-3/screenshots/job_success.png differ
diff --git a/task-3/screenshots/job_success_overview.png b/task-3/screenshots/job_success_overview.png
new file mode 100644
index 0000000..11694b6
Binary files /dev/null and b/task-3/screenshots/job_success_overview.png differ
diff --git a/task-3/screenshots/paused_schedule.png b/task-3/screenshots/paused_schedule.png
new file mode 100644
index 0000000..964b292
Binary files /dev/null and b/task-3/screenshots/paused_schedule.png differ
diff --git a/task-4/BONUSES.md b/task-4/BONUSES.md
new file mode 100644
index 0000000..d292c38
--- /dev/null
+++ b/task-4/BONUSES.md
@@ -0,0 +1,128 @@
+I completed the following optional bonuses:
+
+- [x] Easy — Workflows alerting
+- [x] Medium — Governance
+- [x] Harder — Structured Streaming
+- [ ] Harder+ — Local PySpark module and pytest
+
+## Easy — Workflows alerting
+
+I configured an email notification for failures of the
+`dev_halyna_fct_trips` Databricks Job.
+
+This notification allows pipeline failures to be detected automatically without
+manually checking the Databricks Jobs page after every scheduled run.
+
+![Job failure notification](screenshots/job_notification.png)
+
+## Medium — Governance
+
+### Table privileges
+
+I inspected the access privileges for the table
+`hyf.dev_halyna.fct_trips` using the following SQL command:
+
+```sql
+SHOW GRANTS ON TABLE hyf.dev_halyna.fct_trips;
+
+The result shows the privileges visible to my current Databricks identity. The
+displayed privileges are inherited from the hyf.dev_halyna schema.
+
+## Unity Catalog lineage
+
+I inspected the Unity Catalog lineage graph for
+hyf.dev_halyna.fct_trips.
+
+The graph shows that the final fct_trips table depends on the upstream dbt
+models:
+
+stg_trips
+stg_zones
+
+This lineage information helps identify where the data came from and which
+upstream objects affect the final analytical table.
+
+## Example PII tag
+
+The following statement shows how a hypothetical customer e-mail column could
+be tagged as sensitive personally identifiable information:
+
+ALTER TABLE hyf.dev_halyna.fct_trips
+ALTER COLUMN hypothetical_customer_email
+SET TAGS (
+  'pii' = 'true',
+  'classification' = 'sensitive'
+);
+
+This command was documented but not executed because
+hypothetical_customer_email is not a real column in the fct_trips table.
+
+## Harder — Structured Streaming
+
+I created a Databricks notebook and used the Spark rate source to generate
+streaming rows.
+
+The source generated five rows per second. Each generated record contained:
+
+timestamp
+value
+
+I also added a derived column:
+
+value_squared
+
+The streaming output was written to the following Delta table:
+
+hyf.dev_halyna.rate_stream_demo
+
+A Unity Catalog Volume was used for the Structured Streaming checkpoint because
+the public DBFS root was not available in the shared workspace.
+
+## Streaming dashboard
+
+The streaming dashboard showed the input rate, processing rate, and micro-batch
+duration while the streaming query was active.
+
+## Delta table result
+
+During the demonstration, the stream generated 2,185 rows. The resulting Delta
+table contained the generated timestamp, value, and value_squared
+columns.
+
+## Stopping the stream
+
+After verifying the result, I explicitly stopped the streaming query:
+
+query.stop()
+
+I confirmed that the query was no longer active:
+
+Streaming query active: False
+
+Stopping the query was important because an active streaming process would
+continue generating data and consuming shared compute resources.
+
+I also stopped the idle Spark compute after completing the streaming
+demonstration.
+
+## Harder+ — Local PySpark module and pytest
+
+I created a local PySpark project containing two pure transformation functions:
+
+calculation of trip counts by pickup borough;
+calculation of the average total_amount by payment_type.
+
+The project also contains pytest tests based on small local fixture DataFrames.
+The tests do not read Unity Catalog tables and do not connect to Databricks.
+
+The local project structure was created successfully, and the required Python
+dependencies were installed. However, the tests were not completed successfully.
+
+PySpark requires a local Java Development Kit because the Apache Spark engine
+runs in the Java Virtual Machine. The local Spark session could not start because
+Java was not configured, resulting in this error:
+
+[JAVA_GATEWAY_EXITED] Java gateway process exited before sending its port number.
+
+Because there is no successful green pytest result, I do not claim this bonus
+as completed.
\ No newline at end of file
diff --git a/task-4/pyspark_app/pyproject.toml b/task-4/pyspark_app/pyproject.toml
new file mode 100644
index 0000000..27d0fdf
--- /dev/null
+++ b/task-4/pyspark_app/pyproject.toml
@@ -0,0 +1,18 @@
+[project]
+name = "week13-pyspark-app"
+version = "0.1.0"
+requires-python = ">=3.11,<3.13"
+dependencies = [
+    "pyspark>=3.5,<4.0",
+]
+
+[dependency-groups]
+dev = [
+    "numpy==1.26.4",
+    "pandas>=2.0,<3.0",
+    "pyarrow>=12,<20",
+    "pytest>=8,<9",
+]
+
+[tool.pytest.ini_options]
+pythonpath = ["src"]
diff --git a/task-4/pyspark_app/src/pyspark_app/__init__.py b/task-4/pyspark_app/src/pyspark_app/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/task-4/pyspark_app/src/pyspark_app/transform.py b/task-4/pyspark_app/src/pyspark_app/transform.py
new file mode 100644
index 0000000..0b56d57
--- /dev/null
+++ b/task-4/pyspark_app/src/pyspark_app/transform.py
@@ -0,0 +1,39 @@
+from pyspark.sql import DataFrame
+from pyspark.sql import functions as F
+
+
+def pickup_borough_counts(
+    trips: DataFrame,
+    zones: DataFrame,
+) -> DataFrame:
+    """Count trips for every pickup borough."""
+
+    zone_lookup = zones.select("location_id", "borough")
+
+    return (
+        trips.join(
+            F.broadcast(zone_lookup),
+            trips.pickup_location_id == zone_lookup.location_id,
+            "left",
+        )
+        .groupBy("borough")
+        .agg(F.count("*").alias("trip_count"))
+        .orderBy(F.desc("trip_count"))
+    )
+
+
+def average_total_by_payment(
+    trips: DataFrame,
+) -> DataFrame:
+    """Calculate average total amount per payment type."""
+
+    return (
+        trips.groupBy("payment_type")
+        .agg(
+            F.round(
+                F.avg("total_amount"),
+                2,
+            ).alias("avg_total_amount")
+        )
+        .orderBy("payment_type")
+    )
diff --git a/task-4/pyspark_app/tests/conftest.py b/task-4/pyspark_app/tests/conftest.py
new file mode 100644
index 0000000..1771db1
--- /dev/null
+++ b/task-4/pyspark_app/tests/conftest.py
@@ -0,0 +1,21 @@
+import os
+
+os.environ.setdefault("PYARROW_IGNORE_TIMEZONE", "1")
+
+import pytest
+from pyspark.sql import SparkSession
+
+
+@pytest.fixture(scope="session")
+def spark() -> SparkSession:
+    session = (
+        SparkSession.builder
+        .master("local[2]")
+        .appName("week13-pyspark-tests")
+        .config("spark.ui.enabled", "false")
+        .getOrCreate()
+    )
+
+    yield session
+
+    session.stop()
\ No newline at end of file
diff --git a/task-4/pyspark_app/tests/test_transform.py b/task-4/pyspark_app/tests/test_transform.py
new file mode 100644
index 0000000..0585ee3
--- /dev/null
+++ b/task-4/pyspark_app/tests/test_transform.py
@@ -0,0 +1,72 @@
+from pyspark.testing import assertDataFrameEqual
+
+from pyspark_app.transform import (
+    average_total_by_payment,
+    pickup_borough_counts,
+)
+
+
+def test_pickup_borough_counts(spark):
+    """Count trips for every pickup borough."""
+    trips = spark.createDataFrame(
+        [
+            (1,),
+            (1,),
+            (2,),
+            (3,),
+        ],
+        "pickup_location_id integer",
+    )
+
+    zones = spark.createDataFrame(
+        [
+            (1, "Manhattan"),
+            (2, "Queens"),
+            (3, "Manhattan"),
+        ],
+        "location_id integer, borough string",
+    )
+
+    actual = pickup_borough_counts(trips, zones)
+
+    expected = spark.createDataFrame(
+        [
+            ("Manhattan", 3),
+            ("Queens", 1),
+        ],
+        "borough string, trip_count long",
+    )
+
+    assertDataFrameEqual(
+        actual,
+        expected,
+        checkRowOrder=True,
+    )
+
+
+def test_average_total_by_payment(spark):
+    """Calculate average total amount per payment type."""
+    trips = spark.createDataFrame(
+        [
+            (1, 10.0),
+            (1, 20.0),
+            (2, 30.0),
+        ],
+        "payment_type integer, total_amount double",
+    )
+
+    actual = average_total_by_payment(trips)
+
+    expected = spark.createDataFrame(
+        [
+            (1, 15.0),
+            (2, 30.0),
+        ],
+        "payment_type integer, avg_total_amount double",
+    )
+
+    assertDataFrameEqual(
+        actual,
+        expected,
+        checkRowOrder=True,
+    )
diff --git a/task-4/pyspark_app/uv.lock b/task-4/pyspark_app/uv.lock
new file mode 100644
index 0000000..3f2af98
--- /dev/null
+++ b/task-4/pyspark_app/uv.lock
@@ -0,0 +1,226 @@
+version = 1
+revision = 3
+requires-python = ">=3.11, <3.13"
+resolution-markers = [
+    "python_full_version >= '3.12'",
+    "python_full_version < '3.12'",
+]
+
+[[package]]
+name = "colorama"
+version = "0.4.6"
+source = { registry = "https://pypi.org/simple" }
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