๐ Day 2 of #30DaysOfData! ๐
Mastered Excel sorting & filtering today! Analyzed student performance and uncovered a strong insight: 100% of students with <75% attendance failed their course.
Data speaks volumes! ๐ก
#DataAnalytics#Excel#LearningInPublic#Data
Day 10 of #30DaysOfData! ๐ Automating my database:๐น Procedures: Saved code to easily reuse.
๐น Triggers: Auto-copied new workers to a 2nd list.
๐น Events: Timer to auto-delete old records. Working smarter! ๐ปโจ #SQL#DataAnalytics
Day 9 of #30DaysOfData: CTEs & Temp Tables! ๐
Covered two ways to handle intermediate data in SQL: ๐น Common Table Expressions (CTEs) for cleaner, readable subqueries and multi-table joins ๐น Temporary Tables to store working datasets for a session
#DataAnalytics#SQL
Day 8/30 of my #DataAnalysis challenge! ๐
Today was all about leveling up my SQL skills:
๐น CASE statements for conditional logic
๐น CONCAT() to merge string columns
๐น Stored Procedures with parameters
Building solid foundations! ๐ป๐
#30DaysOfData#SQL#DataAnalytics
Calculating Salary Increases
โขโ โ WHEN salary < 50000 THEN salary * 1.05 gives a 5% raise.
โขโ โ WHEN salary > 50000 THEN salary * 1.07 applies a 7% raise.
โขโ โ Using salary * 0.05 calculates only the raise amount, not the new total!
Day 7 of my 30-Day Data Analysis Challenge! ๐
Dived deep into CASE Statements in SQL today:
โขโ โ Built conditional logic
โขโ โ Chained WHEN...THEN rules
โขโ โ Created column aliases (AS Age_Bracket)
โขโ โ Prevented NULL values
Conditional Logic with CASE
โขโ โ CASE acts like IF/ELSE statements inside your queries.
โขโ โ Evaluates WHEN conditions sequentially from top to bottom.
โขโ โ Returns specific values based on criteria like age <= 30 or BETWEEN 31 AND 50.
Day 6 of my 30-Day Data Analysis Challenge! ๐
Mastered Unions & String Functions in SQL today:
โข Stacked datasets & built custom labels (AS Label)
โข Fixed data type mismatches
โข Standardized text with UPPER(), LOWER() & RTRIM()
โข Sliced strings using LEFT(), RIGHT() & SUBST
Day 4 of #100DaysOfCode / #30DaysOfData ๐
Diving deeper into intermediate SQL querying! Covered: โข GROUP BY & aggregates (AVG, MAX, MIN) โข HAVING (filtering grouped data) โข ORDER BY, LIMIT & Aliasing (AS)
One step closer to mastering database queries! ๐
#SQL#DataAnalytics
So I got accepted into a 6 months Data Science/AI internship and I've been thinking about this a lot
I'm still learning SQL, I haven't even started Power BI yet and my plan has always been to get solid with Excel, SQL and Power BI first and hopefully get a Data Analyst job.
Now look at this curriculum ๐ญ๐
Python, Machine Learning, NLP, GenAI and everything is just waiting for me.
I actually spoke to my mentor about it and he said I should go for it and learn as much as I can, so I've decided to do it.
But I still really want to hear from people already in the data field.
Do you think this is too much to take on this early in my Data Analytics journey?
Or would you take the opportunity and just learn everything along the way?
๐ Wrapped up Day 3 of #30DaysOfData๐ป
SQL Server 2025 & SSMS are fully set up. Tomorrow, we move to the bigger phase: writing queries and diving deep into database operations! ๐
The real fun begins now. ๐ฅ
#DataAnalytics#SQL#LearningInPublic
Day 3/30: Upgraded to SQL! ๐ป
Downloaded SQL Server 2025 & SSMS.
Translating my Excel skills into SQL queries: ๐น Filter โก๏ธ WHERE ๐น Sort โก๏ธ ORDER BY ๐น Summary โก๏ธ AVG / SUM
#30DaysOfData#DataAnalytics#SQLServer