AI Camp: Automated Reporting with SQL - AI-Driven LMS + Atey Tutor

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AI Camp: Automated Reporting with SQL

Categories Automation, Databases, Programming, SQL

Design and build a relational database: Learn to structure databases for efficiency in real-world business scenarios.
Master SQL fundamentals: Gain proficiency in SQL, from basic queries to advanced techniques like JOINs and window functions.
Analyze business data: Create insights from raw data, such as sales trends and inventory management, using SQL.
Automate reports: Use shell scripting and cron jobs to schedule SQL queries for up-to-date business insights.
Optimize performance: Improve query speed and efficiency with optimization and indexing.
Collaborate on projects: Work with an instructor to build an automated reporting system for a small business.

Course Curriculum

Introduction to the Project and Database Fundamentals
Begin by understanding the real-world business dataset and defining the project scope. Learn database fundamentals and design the schema for the project. Students will create the foundational tables and relationships for the database.

CRUD Operations and Populating the Database
Perform CRUD operations (Create, Read, Update, Delete) to populate the database with real-world business data. Write initial queries to insert, retrieve, and update data, laying the groundwork for future analysis.

Querying Data with SELECT and WHERE Clauses
Use the SELECT statement and WHERE clauses to filter and retrieve specific data. Start extracting actionable insights, such as identifying high-performing products or filtering customer activity.

Aggregations and Grouping for Business Insights
Summarize data using aggregation functions (e.g., SUM, AVG, COUNT) and GROUP BY clauses to create reports such as total sales by region or category. These insights will form part of the reporting system.

Advanced Querying with JOIN Operations
Combine data from multiple tables using JOIN operations to answer more complex business questions, like linking customer purchases to product details or inventory levels. These enhanced queries will expand the project’s analytical capabilities.

Advanced Analytics: Window Functions, Subqueries, and Using AI
Implement window functions (e.g., ROW_NUMBER, RANK) and subqueries to generate detailed insights, such as ranking top-performing salespeople or calculating cumulative totals. Experiment with AI tools to help optimize and write SQL queries.

Data Optimization with Indexing and Query Performance
Optimize the project’s queries by creating indexes for faster execution and troubleshooting performance bottlenecks using query execution plans. Students will apply these techniques directly to their project queries.

Automating Reports with SQL and Shell Scripting
Add automation to the project by using shell scripting to run SQL queries and generate reports automatically. Set the foundation for scheduled reporting tasks.

Scheduling Reports with Cron Jobs
Schedule the automated reports created earlier using cron jobs. Ensure the project’s reporting system can generate daily or weekly updates without manual intervention.

Automating Report Outputs
Enhance the project by exporting query results to files (e.g., CSV, JSON) and configuring email notifications to share insights with business stakeholders.

Optimizing Reporting and Adding New Functionality
Refine the reporting system by optimizing workflows and adding customized metrics or new features that align with the project’s business goals, such as additional KPIs or detailed trends.

Capstone: Finalize and Present the Automated Reporting System
Build on the project developed throughout the quarter. Students will demonstrate the fully automated system they’ve created, showcasing their custom additions, such as new metrics, insights, or improved automation workflows.

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Level

All Levels
Duration

72 hours
Last Updated

December 6, 2024
Certificate

Certificate of completion

A course by

DataU Instructor

Instructor

Aspiring data-driven app developers looking to build SQL and automation skills.
Beginners with no prior experience in SQL, eager to learn database management and data analysis.
Professionals in non-technical roles (e.g., marketing, finance) wanting to harness data for better decision-making.
Students pursuing a career in data science, app development, or business analytics.
Anyone interested in solving real-world problems using data and building scalable, data-driven applications.

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