Building Strong SQL Fundamentals for Data Analytics

Week 6 of my Data Analytics Journey Last week, I got introduced to SQL, and I won’t lie, it was confusing at first 😅 I kept asking myself: What exactly am I creating? What am I selecting? But after going back to the class recordings and practicing, things started to make more sense. I learned how to: - Create a database and tables - Define columns and set a primary key - Use SELECT to choose the table I want to work with - Insert values into a table - Delete a row using the primary key. It’s still early, but I’m starting to understand how data is actually stored and managed. Slowly moving from confusion to clarity, one step at a time. @TechCrush.pro #RisewithTechCrush #Tech4Africans #LearningwithTechCrush #DataAnalytics #SQL #LearningJourney #Beginner #Growth #TechSkills

Day 2 – Data Analytics Challenge Topic: SQL JOINs Today I practiced SQL JOINs using a small example. I didn’t try to memorize definitions — I focused on understanding where rows appear and where NULLs come. Example Table A Table B 1 0 null 1 1 null inner join 1 1 1 1 left 1 1 1 1 null null right 1 1 1 1 null 0 null null This is how JOINs differ: INNER → common rows LEFT → inner + remaining rows from left table RIGHT → inner + remaining rows from right table Understanding where NULL appears made JOINs much clearer for me. #DataAnalytics #ExcelDashboard #DataVisualization #LearningInPublic #AnalyticsJourney #DashboardDesign #JaganMohan #LoveWithData #DataAnalyst #Joins

One thing I’m starting to understand about Data Analytics: Data doesn’t become useful just because it exists. Raw data is messy, incomplete, and sometimes misleading. The real value comes from: → Cleaning it → Understanding it → Asking the right questions Only then does it turn into something meaningful. That’s the part I’m focusing on improving every day. #DataAnalytics #Learning #DataThinking #SQL #PowerBI

100 #SQL queries covering real-world scenarios 🚀 From basics to advanced concepts joins, aggregations, window functions, and performance-focused queries this practice pushed my thinking beyond syntax into problem-solving with data. Key takeaway: 👉 #SQL is not just about writing queries, it's about asking the right questions to your data. Consistent practice like this is helping me strengthen my foundation in Data Analytics and prepare for real business use cases. #SQL #DataAnalytics #LearningJourney #PracticeMakesPerfect #AnalyticsWithPraveen

Day 7 of posting about Data Analytics. Ever feel like your SQL data is playing hide-and-seek?String functions are your secret weapon! From cleaning up messy text with TRIM() to extracting just the right info with SUBSTRING(), these functions are incredibly powerful. They help you transform raw data into actionable insights, making your reports look great. Today I revisited a few string functions. What's your go-to SQL string function? Share your favorite in the comments. Mine is CONCAT.I love how it gracefully handles NULLS as opposed to using + #DataAnalytics #SQL #StringFunctions ##Datascience #Techcommunity

🚀 Day 18 of My Data Analytics Journey Today’s focus was on grouping and aggregation in SQL—learning how to summarize data to extract meaningful insights. I worked with the GROUP BY clause alongside aggregate functions like SUM, COUNT, AVG, MIN, and MAX to analyze datasets more effectively. This helped me understand how to break down large volumes of data into smaller, meaningful summaries. I also practiced using HAVING to filter grouped data, which made it possible to focus only on relevant results after aggregation. This step showed me how powerful SQL can be when it comes to analyzing trends and patterns within datasets. What stood out to me is that aggregation transforms raw data into valuable information, making it easier to interpret and support decision-making. I’m becoming more confident in using SQL to not just retrieve data, but to truly analyze it. #DataAnalytics #SQL #DataAggregation #LearningJourney #Day18 #DataDriven

🚀 SQL Scenarios – Day 07 Continuing my journey of solving real-world SQL problems to strengthen my data analytics skills 💻📊 📌 Today’s Focus: ✔️ Custom sorting using CASE WHEN ✔️ Fixing running total calculations using window functions 🔹 What I Practiced Today: 👉 Learned how to force priority rows like “India” to appear first in dashboards using custom sorting 👉 Used CASE WHEN inside ORDER BY to control business-driven report presentation 👉 Understood why running totals behave incorrectly with duplicate values 👉 Fixed cumulative sum issues using ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW 💡 Key Takeaway: Small changes in SQL logic can completely improve reporting accuracy and dashboard presentation — especially in real-world analytics projects. Grateful to Ankit Bansal and Shashank Singh 🇮🇳 Singh for the valuable insights 🙌 #SQL #DataAnalytics #DataAnalyst #SQLPractice #WindowFunctions #LearningJourney #InterviewPreparation #Analytics #SQLTips #LinkedInLearning

I used to think SQL was complicated… But the real problem was simpler than I thought. I wasn’t filtering my data properly I used to run queries on full datasets which made analysis slower and confusing. Then I started using WHERE conditions effectively: • Focus only on relevant data • Reduce unnecessary rows • Get faster and clearer insights Example: SELECT * FROM sales WHERE revenue > 10000; This small change made my queries: ✔ Faster ✔ Cleaner ✔ Easier to understand Now I spend less time searching data and more time analyzing it 📊 Still learning SQL every day as I move into Data Analytics What’s one SQL tip that improved your workflow? #SQL #DataAnalytics #LearningJourney #Analytics

"If you are learning data analytics like me, let’s connect" Today I created a table named "orders" with 4 rows and 5 columns inside my own created database named "revisesql" 💻 It is not the first time I did this kind of work in SQL. Still, I realised that I gain something during my practice each time, resulting in a new version of me ✨ Remembered the line — practice makes man perfect 😊 #KaliyonaSQL #KaliyonaDataAnalytics #KaliyonaWithGayathriBhat

🚀 𝐓𝐡𝐞 𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐒𝐐𝐋 𝐋𝐢𝐞𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐒𝐦𝐚𝐥𝐥𝐞𝐬𝐭 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 Behind every clean dashboard and accurate insight, there’s one common step — data preparation. And when it comes to handling text data, SQL string functions do more than just basic operations… they bring structure to chaos. Using functions like 𝐓𝐑𝐈𝐌(), 𝐒𝐔𝐁𝐒𝐓𝐑𝐈𝐍𝐆(), 𝐋𝐄𝐅𝐓(), 𝐚𝐧𝐝 𝐑𝐈𝐆𝐇𝐓(), you can: ✔ Eliminate inconsistencies ✔ Extract only what matters ✔ Standardize raw text into usable data 💡 These are not just functions — they are the foundation of reliable analysis. #SQL #DataAnalytics #DataCleaning #DataAnalyst #Analytics #LearnSQL