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Zza Data

Zza Data is sample data for a fictive pizza takeout and delivery chain named Zza. Here is Zza himself!

Zza

Zza Data is also a pure JavaScript application for generating that data in a variety of formats. Today it supports three formats:

  • JSON
  • SQL Server (T-SQL)
  • Mongo

We hope it supports more formats in time. Send in your pull requests.

Why Zza?

We build many forms-over-data sample applications. The data model for such apps has to be simple enough to understand quickly but rich enough to represent typical scenarios for forms-over-data applications. We wanted something fresher and more fun than that tired old Microsoft Northwind database. We couldn't find anything so we wrote "zza.data".

We want to share it with you, so you can build your own sample apps without having to waste time (like we did) dreaming up a data model, populating a database with sample data, and having to explain its schema and contents to the world. We all want to move on to the fun stuff, the application itself.

The Zza project is just underway and of course the documentation lags behind the project code. Here's what we can tell you now.

The Zza Story

Zza takes orders over the phone for pick-up and delivery; perhaps in your app, the Customer can order online. The customer self-identifies by name (“Skippy”) and phone number. If the customer wants the order delivered, s/he supplies a delivery address.

The customer places an Order for pizzas, salads, and drinks. The app remembers the customers and their orders.

The customer picks from a Product catalog of pizzas, salads, and drinks. S/he can customize pizzas and salads (Products) with toppings (ProductOptions). The resulting order is a three level structure: Order -> OrderItem -> OrderItemOption.

Pricing is a bit tricky ... deliberately. The pizzas and salads come in different sizes, each size with its own price for the base pizza/salad and a price per extra topping. Some of the toppings are free (spices). Some of the toppings cost double the topping-price-per-product-size (Pesto, BBQ Chicken). The parameters of the calculation are captured in properties of the ProductSize, Product and ProductOption entities.

There are a few more wrinkles (gluten-free costs more, $2 for delivery). You can read the code in "zzaGenerator.js" yourself (we'll explain these pricing and other 'rules' in more detail in future).

The rules don't really matter. The point is to introduce enough complexity so you can demonstrate how you'd implement and represent business rules in your application.

The primary keys are all called id. They are all integer ... except the Customer id which is a Guid in the JSON and SQL generations and is an ObjectId in the MongoDb generation. We needed a little variety for extra "realism".

The Customer has an address because s/he might order again. But the order has its own delivery address because ... well, you might order a pizza while you're at your friend's house; you don't want Zza to deliver it to your home, right?

The Model

We need the following "Entity Types" to make this work. Here are the entity type names and current number of items generated for each type.

Mutable Entities

  • Customer (100)
  • Order (513)
  • OrderItem (1447 ordered pizzas, salads, and drinks)
  • OrderItemOption (1773 ordered crusts, toppings, and salad dressings)

Reference Entities

  • OrderStatus (5: Ordered, PickedUp, Delivered, Canceled, Pending)
  • Product (41 pizzas, salads, and drinks)
  • ProductOption (64 crusts, toppings, and salad dressings)
  • ProductSize (15)

SQL v No-SQL

Those entities map one-for-one to SQL tables and there are foreign keys to support the associations among related entities.

It wouldn't be any fun if they also mapped one-for-one to Mongo collections. So they don't. Each Order is a document with a collection of OrderItems, and each of them has a collection of OrderItemOptions. Naturally some of the data are denormalized. For example, you'll find the customer name repeated in each order. The Order document is optimized for the application's checkout screen and to tell the kitchen staff how to fill your order.

Get the data

Launch index.html in a browser and click one of the generator buttons to produce the JSON or T-SQL script for the Zza database. The output appears in a scrollable box on screen. Click the [Select all] button and copy the output; paste it wherever it's useful to you.

For example, you could paste the JSON output into a new JavaScript file in your project and use that as the basis for mock data objects while you're developing your front-end.

You could run the "T-SQL" generator, open SQL Server Management Studio (SMS), create a new "Zza" database, open a new query window, paste, and execute. It should populate your new Zza database for you. You'll also find a recent generation of the T-SQL script in the output folder as "ZzaDatabaseGen.sql"; you can just play that SQL script in Visual Studio or in SQL SMS.

The mongo generator is a little different. It requires node.js. Assuming you have node and MongoDb installed, you fire up your MongoDb server and then run "mongoGen.js" in node. That will (re)create a "Zza" database.

Or you could extract "ZzaMongDb.zip" (located in the output folder) into your MongoDb data folder.

Images

You want pictures in your app, right? We've got Product pictures of pizzas, salads and drinks in the images folder.

pizza   pizza   pizza

Feel free to contribute better ones (the drinks are all the same at the moment).

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Build your sample app with ready-made data for a fictive pizza takeout and delivery chain named "Zza"

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