📊 Data Science Essentials: What Every Data Enthusiast Should Know!

1️⃣ Understand Your Data
Always start with data exploration. Check for missing values, outliers, and overall distribution to avoid misleading insights.

2️⃣ Data Cleaning Matters
Noisy data leads to inaccurate predictions. Standardize formats, remove duplicates, and handle missing data effectively.

3️⃣ Use Descriptive & Inferential Statistics
Mean, median, mode, variance, standard deviation, correlation, hypothesis testing—these form the backbone of data interpretation.

4️⃣ Master Data Visualization
Bar charts, histograms, scatter plots, and heatmaps make insights more accessible and actionable.

5️⃣ Learn SQL for Efficient Data Extraction
Write optimized queries (SELECT, JOIN, GROUP BY, WHERE) to retrieve relevant data from databases.

6️⃣ Build Strong Programming Skills
Python (Pandas, NumPy, Scikit-learn) and R are essential for data manipulation and analysis.

7️⃣ Understand Machine Learning Basics
Know key algorithms—linear regression, decision trees, random forests, and clustering—to develop predictive models.

8️⃣ Learn Dashboarding & Storytelling
Power BI and Tableau help convert raw data into actionable insights for stakeholders.

🔥 Pro Tip: Always cross-check your results with different techniques to ensure accuracy!

DOUBLE TAP ❤️ IF YOU FOUND THIS HELPFUL!

When starting off your data analytics journey you DON'T need to be a SQL guru from the get-go.

In fact, most SQL skills you will only learn on the job with:

- real business problems.
- actual data sets.
- imperfect data architecture.
- other people to collaborate with.

So be kind to yourself, give yourself time to grow and above all...

try to become proficient at SQL rather than perfect.

The rest will take care of itself along the way! 😉

SQL Cheatsheet 📝

This SQL cheatsheet is designed to be your quick reference guide for SQL programming. Whether you’re a beginner learning how to query databases or an experienced developer looking for a handy resource, this cheatsheet covers essential SQL topics.

1. Database Basics
- CREATE DATABASE db_name;
- USE db_name;

2. Tables
- Create Table: CREATE TABLE table_name (col1 datatype, col2 datatype);
- Drop Table: DROP TABLE table_name;
- Alter Table: ALTER TABLE table_name ADD column_name datatype;

3. Insert Data
- INSERT INTO table_name (col1, col2) VALUES (val1, val2);

4. Select Queries
- Basic Select: SELECT * FROM table_name;
- Select Specific Columns: SELECT col1, col2 FROM table_name;
- Select with Condition: SELECT * FROM table_name WHERE condition;

5. Update Data
- UPDATE table_name SET col1 = value1 WHERE condition;

6. Delete Data
- DELETE FROM table_name WHERE condition;

7. Joins
- Inner Join: SELECT * FROM table1 INNER JOIN table2 ON table1.col = table2.col;
- Left Join: SELECT * FROM table1 LEFT JOIN table2 ON table1.col = table2.col;
- Right Join: SELECT * FROM table1 RIGHT JOIN table2 ON table1.col = table2.col;

8. Aggregations
- Count: SELECT COUNT(*) FROM table_name;
- Sum: SELECT SUM(col) FROM table_name;
- Group By: SELECT col, COUNT(*) FROM table_name GROUP BY col;

9. Sorting & Limiting
- Order By: SELECT * FROM table_name ORDER BY col ASC|DESC;
- Limit Results: SELECT * FROM table_name LIMIT n;

10. Indexes
- Create Index: CREATE INDEX idx_name ON table_name (col);
- Drop Index: DROP INDEX idx_name;

11. Subqueries
- SELECT * FROM table_name WHERE col IN (SELECT col FROM other_table);

12. Views
- Create View: CREATE VIEW view_name AS SELECT * FROM table_name;
- Drop View: DROP VIEW view_name;

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