Data Warehousing
  • Data Warehousing
  • Readme
  • Fundamentals
    • Terms to Know
    • Jobs
    • Skills needed for DW developer
    • Application Tiers
    • Operational Database
    • What is a Data Warehouse
      • Typical Data Architecture
      • Problem Statement
      • Features of Data Warehouse
      • Need for Data Warehouse
      • Current State of the Art
    • Activities of Data Science
    • Types of Data
    • Data Storage Systems
    • Data Warehouse 1980 - Current
    • Data Warehouse vs Data Mart
    • Data Warehouse Architecture
      • Top-Down Approach
      • Bottom-Up Approach
    • Data Warehouse Characteristic
      • Subject Oriented
      • Integrated
      • Time Variant
      • Non Volatile
    • Tools
    • Cloud vs On-Premise
    • Steps to design a Data Warehouse
      • Gather Requirements
      • Environment
      • Data Modeling
      • Choosing ETL / ELT Solution
      • Online Analytic Processing
      • Front End
      • Query Optimization
    • Dataset Examples
    • Thoughts on some data
  • RDBMS
    • Data Model
      • Entity Relationship Model
      • Attributes
      • Keys
      • Transaction
      • ACID
    • Online vs Batch
    • DSL vs GPL
    • Connect to Elvis
    • SQL Concepts
      • Basic Select - 1
      • Basic Select - 2
      • UNION Operators
      • Wild Cards & Distinct
      • Group By & Having
      • Sub Queries
      • Derived Tables
      • Views
    • Practice using SQLBolt
  • Cloud
    • Overview
    • Types of Cloud Services
    • Challenges of Cloud Computing
    • AWS
      • AWS Global Infrastructure
      • EC2
      • S3
      • IAM
    • Terraform
  • Spark - Databricks
    • Storage Formats
    • File Formats
    • Medallion Architecture
    • Delta
  • Data Warehousing Concepts
    • Dimensional Modelling
      • Star Schema
      • Galaxy Schema
      • Snowflake Schema
      • Starflake Schema
      • Star vs Snowflake
      • GRAIN
      • Multi-Fact Star Schema
      • Vertabelo Tool
    • Dimension - Fact
    • Sample Excercise
    • Keys
      • Why Surrogate Keys are Important
    • More Examples
    • Master Data Management
    • Steps of Dimensional Modeling
    • Types of Dimensions
      • Date Dimension Table
      • Degenerate Dimension
      • Junk Dimension
      • Static Dimension
      • Conformed Dimensions
      • Slowly Changing Dimensions
        • SCD - Type 0
        • SCD - Type 1
        • SCD - Type 2
        • SCD - Type 3
        • SCD - Type 4
        • SCD - Type 6
        • SCD - Type 5 - Fun Fact
      • Role Playing Dimension
      • Conformed vs Role Playing
      • Shrunken Dimension
      • Swappable Dimension
      • Step Dimension
    • Types of Facts
      • Factless Fact Table
      • Transaction Fact
      • Periodic Fact
      • Accumulating Snapshot Fact Table
      • Transaction vs Periodic vs Accumulating
      • Additive, Semi-Additive, Non-Additive
      • Periodic Snapshot vs Additive
      • Conformed Fact
    • Sample Data Architecture Diagram
    • Data Pipeline Models
    • New DW Concepts
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  1. Fundamentals

Dataset Examples

Retail Sales Transactions: This dataset includes individual retail store or chain sales transactions. It typically contains transaction ID, customer ID, product ID, quantity, price, and timestamp.

Transaction ID
Customer ID
Product
Quantity
Price
Timestamp

T001

C001

Apple iPhone X

5

$10.99

2023-05-10 10:30:15

T002

C002

Samsung Galaxy S9

3

$24.99

2023-05-10 14:45:21

T003

C003

HP Printer

2

$5.99

2023-05-11 09:12:33

Financial Transactions: This dataset consists of financial transactions from banks or credit card companies. It includes transaction ID, account number, transaction type, amount, merchant information, and timestamp.

Transaction ID
Account Number
Transaction Type
Amount
Merchant
Timestamp

T001

A123456

Deposit

$100.00

XYZ Bank

2023-05-10 08:15:30

T002

B987654

Withdrawal

-$50.00

ABC Store

2023-05-10 15:20:45

T003

C246810

Transfer

$250.00

Online Shopping

2023-05-11 11:05:12

Online Marketplace Transactions: This dataset contains transactions from an online marketplace like Amazon, eBay, or Alibaba. It includes transaction ID, buyer/seller ID, product ID, quantity, price, shipping details, and timestamps.

Transaction ID
Buyer
Seller
Product
Quantity
Price
Shipping Details
Timestamp

T001

John Doe

SellerA

Book

1

$19.99

Address1, City1, State1

2023-05-10 13:45:27

T002

Jane Smith

SellerB

Smartphone

2

$49.99

Address2, City2, State2

2023-05-10 16:20:10

T003

Mark Johnson

SellerC

Headphones

3

$9.99

Address3, City3, State3

2023-05-11 10:05:55

E-commerce Order Transactions: This dataset focuses on transactions from an e-commerce website. It includes data such as order ID, customer ID, product ID, quantity, price, shipping information, payment details, and timestamps.

Order ID
Customer
Product
Quantity
Price
Shipping Information
Payment Details
Timestamp

O001

John Doe

Apple iPhone X

2

$29.99

Address1, City1, State1

Credit Card

2023-05-10 11:30:45

O002

Jane Smith

Samsung Galaxy S9

1

$14.99

Address2, City2, State2

PayPal

2023-05-10 17:15:20

O003

Mark Johnson

HP Printer

4

$39.99

Address3, City3, State3

Credit Card

2023-05-11 08:45:10

Travel Booking Transactions: This dataset comprises transactions from a travel booking website or agency. It includes booking ID, traveler details, flight/hotel ID, dates, prices, payment information, and timestamps.

Booking ID
Traveler
Flight
Hotel
Dates
Price
Payment Information
Timestamp

B001

John Doe

Flight 123

Hotel ABC

2023-06-15 - 2023-06-20

$500.00

Credit Card

2023-05-10 09:30:15

B002

Jane Smith

Flight 456

Hotel XYZ

2023-07-01 - 2023-07-10

$750.00

PayPal

2023-05-11 14:20:30

B003

Mark Johnson

Flight 789

Hotel PQR

2023-08-10 - 2023-08-15

$600.00

Credit Card

2023-05-12 11:45:55

Stock Market Transactions: This dataset involves transactions from stock exchanges. It includes details like trade ID, stock symbol, buy/sell order, quantity, price, trader information, and timestamps.

Transaction ID
Stock Symbol
Buy/Sell
Quantity
Price
Trader
Timestamp

T001

AAPL

Buy

100

$150.50

John Doe

2023-05-10 09:30:15

T002

GOOGL

Sell

50

$2500.00

Jane Smith

2023-05-10 11:15:45

T003

MSFT

Buy

75

$180.75

Mark Johnson

2023-05-10 14:40:20

Popular API Sources

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Last updated 1 year ago

https://developer.spotify.com/documentation/web-api
https://developer.marvel.com/
https://developers.google.com/youtube/
https://www.openfigi.com/api