Basic Data Exploration and Reporting Using SQL
Group Category: Use Case
Product Category: Database Design & Development
Sub Category: PostgreSQL
Learn how to explore platform metrics and generate clear reports using SQL and real music data.
Business Overview:
Basic Data Exploration and Reporting Using SQL is designed to help beginners understand how to use SQL for generating business insights from real-world music streaming data. You’ll explore high-level platform stats like total users, top-performing artists, album timelines, and genre trends. This product is ideal for those starting out with SQL, looking to learn how to structure queries, generate reports, and answer fundamental business questions using clean, well-organized data.
Product Highlights:
- Beginner-friendly PDF guide featuring 5 foundational SQL reporting use cases
- Covers metrics such as user registration trends, song counts by artist, and content distribution by genre
- Uses a relational dataset of 25,000+ rows simulating music platform data (users, artists, albums, songs, genres, playlists)
- Great starting point for learners looking to build confidence in SQL for dashboards, KPIs, and summaries
- A valuable entry-level project for portfolios showcasing SQL-based reporting and data exploration
Learning Outcomes:
By completing this product, you’ll gain practical skills in:
- Using aggregate functions to generate platform KPIs
- Applying
GROUP BYandORDER BYclauses for summary reports and rankings - Writing subqueries to display multiple summary statistics in a single result
- Extracting and grouping data by time using Date and Time functions
- Structuring SQL queries that produce clean, business-ready reports for stakeholder use
Use Case Document
| PDFDescription:
This PDF introduces a beginner-friendly approach to SQL-driven data exploration within the context of a music streaming platform. It walks users through foundational reporting techniques to generate platform-level insights using structured queries.
- Contains defined use cases with clear business goals, SQL focus areas, and expected results
- Guides learners in writing descriptive SQL queries using joins, aggregation, and date functions
- Useful for understanding user growth, content distribution, and performance metrics
- Supports beginner SQL training, dashboard prototyping, and report automation workflows
- Complements music platform datasets for generating high-level summaries and usage insights
albums
| CSVDescription:
This file catalogs albums in the music platform, enabling content grouping and performance tracking at the album level.
- Contains album IDs, names, and associated artist references
- Serves as a structural layer for organizing songs into collections
- Essential for analyzing release patterns, artist output, and content lifecycle
- Supports timeline reporting and content planning workflows
- Complements songs and artists datasets for full catalog analysis
artists
| CSVDescription:
This file maintains detailed identity records of music creators, forming the backbone for artist-based content and performance analysis.
- Includes artist IDs and names
- Serves as the foundational reference for songs, albums, and playlists
- Essential for linking musical output with individual or group creators
- Enables segmentation by popularity, genre, or content volume
- Supports artist profiling and content discovery logic
genres
| CSVDescription:
This dataset provides standardized genre labels, forming the classification system for organizing and analyzing music content.
- Contains genre IDs and names
- Enables genre-based filtering, sorting, and user interest tagging
- Essential for personalization, curation, and recommendation engines
- Supports high-level trend tracking across content types
- Complements songs and playlists for content enrichment
playlists
| CSVDescription:
This file captures structured data on playlists, enabling curation tracking and playlist-level engagement analysis.
- Includes playlist IDs, titles, creator info, and creation timestamps
- Serves as the organizing unit for grouped songs curated by users or the system
- Essential for understanding user preferences and social music behavior
- Supports playlist ranking, growth tracking, and follower insights
- Integrates with playlist_songs and user data for full engagement analysis
song_genres
| CSVDescription:
This dataset maps songs to one or more genres, enriching content with classification metadata for advanced filtering and discovery.
- Contains song IDs with genre associations
- Supports multi-genre tagging, diversity analysis, and recommendation input
- Essential for content-based filtering and cross-genre trend mapping
- Enables richer song profiles for algorithmic and manual curation
- Complements songs and genres datasets for tagging and exploration
songs
| CSVDescription:
This file includes detailed records of individual songs, serving as the core dataset for streaming content.
- Contains song IDs, names, durations, and references to albums and artists
- Forms the foundation for user interaction, playback, and analytics
- Essential for understanding content performance and popularity
- Supports reporting on consumption patterns, content gaps, and catalog strength
- Complements playlists, genres, and listening behavior datasets
users
| CSVDescription:
This dataset captures the demographic and account metadata of platform users, forming the base for personalization and behavioral analysis.
- Includes user IDs, usernames, and account registration data
- Enables segmentation for engagement tracking and user cohort creation
- Essential for linking user behavior with preferences and playback history
- Supports user lifecycle analysis and personalization systems
- Complements playlist creation, listening behavior, and follow datasets
$1.45 $1.00 31% OFF
About this Dataset:
Similar Products
Read All The Top User Reviews
Loading ratings and reviews...
No reviews yet
Be the first to review this product!
Error loading reviews
Please try refreshing the page.