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29. Practice Exercises and Final Assignment

29.13 Final Assignment: "Blinkit vs Amazon Now – City Performance Report"

Plan the final assignment before you build — example — in 30 seconds

What: Before you build the final assignment, turn each requirement into a measure, a visual and a page, on paper.

Why: Students start dragging charts and miss half the brief. A plan table keeps every requirement covered.

Tiny example: Requirement "Compare platforms by city", then measure Total Sales, then clustered column chart with Legend = Platform.

First look at the data (before, then after):

Plan the final assignment before you build — example: before and after tables, fictional Blinkit Maharashtra data

Same before / after tables as text

Before — Brief lines (Blinkit vs Amazon Now – City Performance Report)

# Requirement
1 Total sales and orders for each platform
2 Compare platforms by city
3 Show the % of orders delivered under 10 minutes
4 City managers see only their city

About this data: This table uses columns: Measure, Visual, Page. This table uses columns: Area, Weight. Values shown are the lesson examples already on this page (not a new dataset).

Formula / click path

For each requirement: measure, then visual, then page, then check one number by hand

After — Plan table

# Measure Visual Page
1 Total Sales, Total Orders Cards + Platform slicer Overview
2 Total Sales Clustered column: City, Legend = Platform Overview
3 % Orders Delivered Under 10 Mins Bar by city, sorted Delivery
4 — RLS role on DarkStore[City] Modeling › Manage roles

Do it step by step:

  1. Copy every line of the brief into column 1 of a plan table.
  2. For each line, write the measure you need.
  3. Write the visual next to it.
  4. Write the page it lives on.
  5. Build page by page. Tick a line only after you check one number by hand.
  6. Finish with an RLS test (View as) and a Performance Analyzer run.

Scenario. The (fictional) leadership team wants to review quick-commerce performance for the Indian financial year (April–March) across Pune, Nashik, Nagpur, Kolhapur, Mumbai and Sambhaji Nagar, and compare Blinkit with Amazon Now. Use only the fictional sample data.

Requirements:

  1. Data preparation: use parameters for the folder path and start date; combine monthly Blinkit files with the Folder connector; standardise city spellings with a mapping table; flag invalid values; clean and rename the Amazon Now file and append it; add Order Date, Order Hour and Delivery Band; remove errors and duplicates; document every applied step with meaningful names.
  2. Model: star schema with Orders, Product, Customer, DarkStore, DeliveryPartner and a DAX Date table with Fiscal Year and Fiscal Quarter; inactive Delivered Date relationship; all keys hidden; Location, Date and Product hierarchies; a Region group; a _Measures table with display folders.
  3. Measures (minimum 18): base measures, AOV, Cancellation Rate, Avg Delivery Time, % Orders Delivered Under 10 Mins, Orders per Dark Store, Repeat Customer %, FYTD sales (TOTALYTD with "3/31"), sales last FY YTD, YoY %, 7-day moving average of orders, store speed rank, top 5 product share, platform share %, dynamic title.
  4. Report (minimum 4 pages + 1 drill-through + 1 tooltip page): executive overview, delivery operations, customers & products, and a Blinkit vs Amazon Now comparison page – with synced slicers, a page navigator menu, a show/hide filter panel, bookmarks, drill down on the Location hierarchy, dynamic titles, conditional colours (delivery time > 15 min red), a dark store map, a dynamic Top N chart and at least one field parameter.
  5. Security: dynamic RLS for city managers (Ravindra Bagale – Pune, Shraddha Bagale – Nashik, Shahrukh – Nagpur, Zoya – Kolhapur, Amir – Mumbai, Raja – Sambhaji Nagar; Ravina sees Pune and Mumbai).
  6. Service: publish, create a dashboard with 4 pinned tiles, one alert, one subscription and an app (if your licence allows).
  7. Presentation: a 5-minute walkthrough explaining 3 insights from your sample data and 3 design decisions.

Evaluation guide for trainers:

Area Weight
Data preparation and documentation 15%
Data model design 20%
DAX correctness and readability 25%
Report design, storytelling and accessibility 25%
Security, Service configuration and presentation 15%

Do not rush the final assignment. Finish one step, check it, then move on. All the best!

Ravindra Bagale's Tip

Friends, many students try to build the final assignment in one sitting and get stuck. Split it into the steps of Module 28, finish and check each step, and keep a short log of decisions (KPI definitions, assumptions) that you can explain in an interview. Never forget this.

Thodkyaat sangaycha tar (quick recap)

Do every exercise yourself, compare your results with the source, and do the final assignment with the steps of Module 28. Now let us move on to interview preparation.

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