SQL Challenge: Matching 'C' in Skills Column

𝐃𝐚𝐲 12/30: 𝐅𝐢𝐥𝐥𝐢𝐧𝐠 𝐔𝐩 𝐭𝐡𝐞 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐖𝐢𝐭𝐡 𝐑𝐞𝐚𝐥 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 🏢 𝘛𝘰𝘥𝘢𝘺 𝘐 𝘢𝘥𝘥𝘦𝘥 19 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘵𝘰 𝘮𝘺 𝘰𝘯𝘭𝘪𝘯𝘦 𝘥𝘢𝘵𝘢𝘣𝘢𝘴𝘦. 𝐖𝐡𝐚𝐭 𝐈 𝐝𝐢𝐝: Wrote a quick Python script that created company names, job listings, and passwords for each one. This gives me real-looking data to test with, instead of empty pages. 𝐓𝐡𝐞 𝐬𝐭𝐫𝐮𝐠𝐠𝐥𝐞: Took a few tries to get it right. My database structure is strict, so if anything was missing or in the wrong spot, it rejected the whole thing. 𝐋𝐞𝐬𝐬𝐨𝐧: Test data is a lifesaver. It shows you problems before real users do. But your data has to follow the rules exactly, or the database won’t accept it. #30DaysOfCode #BuildingInPublic #Database #Python #TechJourney #Typescript #react #supabase #fullstack

Day 03 #StudyClub SQL, we performed data transformation and loaded the data into the database we created on Day 02. This time, we used Python for the transformation and loading process into MySQL. Stay tuned for the next episode to find out the results and the ultimate goal of this #StudyClub SQL episode. Fyi, we successfully load 72 million records of data. We encountered many errors and issues during this process. I've already written down all the issues and their solutions in the report. Mentor: Hilmi ‎. Team: Monika Hermiani Yolanda Simamora Irpan Pilihan Rambe nadhira M. Aprida Sapitri Br Saragih Dyah Ayu Goldy Cahyastuti Medina Uli Alba Somala Siti Komala Hafsaninda MR Rintaldi Ghazian Hindami Reihan Nanda R. #SQLDay #MySQL #EntityRelationshipDiagram #ManifoldDatafolk #DatabaseDesignPrinciple #StudyClubDay3 #Python #ETLProcess

𝗢𝗻𝗲 𝘀𝗺𝗮𝗹𝗹 𝗲𝗿𝗿𝗼𝗿 𝘁𝗮𝘂𝗴𝗵𝘁 𝗺𝗲 𝗮 𝗯𝗶𝗴 𝗹𝗲𝘀𝘀𝗼𝗻 𝗮𝗯𝗼𝘂𝘁 𝗱𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 🚀 Today while solving a SQL problem on LeetCode, I ran into this: TypeError: write() argument 1 must be unicode, not str At first glance, it looked like I had completely messed up. I rechecked my query. Tried different approaches. Still the same error. Then I realized the real issue… I had used ROWID — which works perfectly in Oracle. But LeetCode runs on MySQL, where ROWID doesn’t exist. And instead of a clear SQL error, it threw a Python error. That’s what made it confusing. That moment taught me something important: Not all errors mean your logic is wrong. Sometimes, you just need to understand the environment you’re working in. Debugging isn’t only about fixing code… It’s about thinking deeper and asking the right questions. Back to learning 🚀 #SQL #Debugging #LeetCode #BackendDevelopment #LearningJourney #ProblemSolving

🎯 Tech Learning Journey - Day 09: SQLite Databases - Your Personal Data Vault! SQLite is like having a mini database built right into Python. It's a lightweight database that stores data in tables you can search, filter, and update - perfect for apps that need to remember information between runs. import sqlite3 # Create database and table conn = sqlite3.connect\('mydata.db'\) cursor = conn.cursor\(\) cursor.execute\('CREATE TABLE IF NOT EXISTS users \(id INTEGER PRIMARY KEY, name TEXT\)'\) # Insert and query data cursor.execute\("INSERT INTO users \(name\) VALUES \('Dhanush'\)"\) cursor.execute\("SELECT \* FROM users"\) print\(cursor.fetchall\(\)\) # \[\(1, 'Dhanush'\)\] conn.close\(\) Where I use this: Building apps that need persistent storage, logging user activity, and managing application data locally. #Python #Coding #Programming #Database #SQLite

Day 10/30 — Social Network Analyzer (Python + MySQL) 🔹 Project Overview: Developed a Social Network Analyzer system using Python and MySQL to model user relationships, analyze connections, and recommend new links using graph-based algorithms. 🔹 Tools Used: Python | MySQL | Data Structures | Graph Algorithms | NetworkX | Matplotlib 🔹 Key Features: • Designed relational database to manage users and connections • Built graph structure to represent real-world relationships • Implemented BFS to find shortest connection paths • Identified mutual connections between users • Developed recommendation engine based on shared connections • Added network visualization for interactive analysis • Created CLI-based interface with clean and colored output 🔹 What I Learned: • Applying graph algorithms in real-world scenarios • Working with MySQL for structured data management • Building scalable backend logic using Python • Visualizing relationships using network graphs • Designing modular and maintainable code 🔗 GitHub Repository: https://lnkd.in/dpSCzhQG Would appreciate your feedback and suggestions 🙌 #30DaysOfCoding #PythonProjects #SQL #DataStructures #BackendDevelopment #LearningByDoing

I was loading CSV files into SQL Server. It was slow. Then I switched to BULK INSERT. 💥 Everything changed. BULK INSERT is a native SQL method. It is built for speed. But the real power comes when you combine it with Python. 𝗪𝗵𝗮𝘁 𝗱𝗶𝗱 𝗜 𝗱𝗼? ✔️ Python to handle multiple CSV files ✔️ Python to clean and normalize data ✔️ BULK INSERT for fast loading into SQL Server This combination is simple. And very powerful. Python manages flexibility. SQL manages performance. 𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁: a faster ingestion process a cleaner pipeline a more reliable system 𝗗𝗮𝘁𝗮 𝗶𝗻𝗴𝗲𝘀𝘁𝗶𝗼𝗻 𝗶𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗹𝗼𝗮𝗱𝗶𝗻𝗴. 𝗜𝘁’𝘀 𝗮𝗯𝗼𝘂𝘁 𝘀𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝗰𝗼𝗻𝘁𝗿𝗼𝗹. Curious how it works? 🔗 GitHub repository: https://lnkd.in/dwjwP-bh P.S.  I know BULK sounds a lot like “HULK”… not very original, but I like it 😄

Every new skill starts with confusion, errors, and a lot of debugging. Working with SQL connections and PostgreSQL through Python has been exactly that—figuring out errors, understanding why queries fail, and learning how databases actually function. But that’s also where the real learning happens. Step by step, I’m becoming more comfortable with querying data, managing connections, and thinking more logically about how information is stored and retrieved. It’s a process, but one that’s building a solid foundation for data analytics and future work in finance. #SQL #PostgreSQL #Python #DataAnalytics #DataScience #Finance #LearningByDoing #MittalschoolofBusiness #lpu

🚀 Day 1 of SQL Series! Starting from the absolute basics — because strong fundamentals beat shortcuts every time. Today I covered: ✅ What is SQL & DBMS ✅ Types of SQL Commands (DDL, DML, DQL, DCL, TCL) ✅ SQL Datatypes (CHAR, VARCHAR, NUMBER, DATE, CLOB, BLOB) One image. Everything you need to know on Day 1. Drop a 🔥 if you're learning SQL too! #SQL #DataScience #100DaysOfCode #LearningInPublic #Python #Database

Day 04 #StudyClub SQL, we learned and implemented indexing strategies. The purpose of this indexing is to reduce the time it takes for the database to process our queries, due to the large volume of data. With 72 million records, processing a single query without an index would take an extremely long time. Mentor: Hilmi ‎. Team: Monika Hermiani Yolanda Simamora Irpan Pilihan Rambe nadhira M. Aprida Sapitri Br Saragih Dyah Ayu Goldy Cahyastuti Medina Uli Alba Somala Siti Komala Hafsaninda MR Rintaldi Ghazian Hindami Reihan Nanda R. #SQLDay #MySQL #EntityRelationshipDiagram #ManifoldDatafolk #DatabaseDesignPrinciple #StudyClubDay4 #Python #ETLProcess #IndexingStrategies

Continuing from last week’s report, this week I learned about SQL and Git. I had some experience with databases before using Python, but mostly limited to CRUD. So at first, I thought SQL would be similar. Turns out, it’s much more than that. Here are some key things I learned this week: • Basic SQL (DDL, DML, queries like SELECT, WHERE, etc.) • Data processing using aggregate functions & GROUP BY • Joining multiple tables using JOIN • Version Control System (Git) and its workflow • Using GitHub for collaboration and tracking changes This made me realize that SQL is not just about CRUD, but about structuring and processing data more effectively. Still learning, but turns out it’s starting to make more sense why these fundamentals matter. If you’re interested, feel free to check out the slides I’ve shared. #DigitalSkola #LearningProgressReview #DataScience