Data Analytics

Few ways to optimise SQL Queries👇👇 Use Indexing: Properly indexing your database tables can significantly speed up query performance by allowing the database to quickly locate the rows needed for a query. Optimize Joins: Minimize the number of joins and use appropriate join types (e.g., INNER JOIN, LEFT JOIN) to ensure efficient data retrieval. Avoid SELECT * : Instead of selecting all columns using SELECT *, explicitly specify only the columns needed for the query to reduce unnecessary data transfer and processing overhead. Use WHERE Clause Wisely: Filter rows early in the query using WHERE clause to reduce the dataset size before joining or aggregating data. Avoid Subqueries: Whenever possible, rewrite subqueries as JOINs or use Common Table Expressions (CTEs) for better performance. Limit the Use of DISTINCT: Minimize the use of DISTINCT as it requires sorting and duplicate removal, which can be resource-intensive for large datasets. Optimize GROUP BY and ORDER BY: Use GROUP BY and ORDER BY clauses judiciously, and ensure that they are using indexed columns whenever possible to avoid unnecessary sorting. Consider Partitioning: Partition large tables to distribute data across multiple nodes, which can improve query performance by reducing I/O operations. Monitor Query Performance: Regularly monitor query performance using tools like query execution plans, database profiler, and performance monitoring tools to identify and address bottlenecks. React ❤️ for more

Data Analyst Interview QnA 1. Find avg of salaries department wise from table. Answer- SELECT department_id, AVG(salary) AS avg_salary FROM employees GROUP BY department_id; 2. What does Filter context in DAX mean? Answer - Filter context in DAX refers to the subset of data that is actively being used in the calculation of a measure or in the evaluation of an expression. This context is determined by filters on the dashboard items like slicers, visuals, and filters pane which restrict the data being processed. 3. Explain how to implement Row-Level Security (RLS) in Power BI. Answer - Row-Level Security (RLS) in Power BI can be implemented by: - Creating roles within the Power BI service. - Defining DAX expressions that specify the data each role can access. - Assigning users to these roles either in Power BI or dynamically through AD group membership. 4. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys. Answer - d = {'apple': 2, 'banana': 5} d['orange'] = 3 # Add element d['apple'] = 4 # Modify element sorted_d = dict(sorted(d.items())) # Sort dictionary print(sorted_d) 5. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated. Answer - from collections import Counter numbers = [1, 2, 2, 3, 4, 5, 1, 6, 7, 3, 8, 1] count = Counter(numbers) duplicates = {k: v for k, v in count.items() if v > 1} print(duplicates)

Python Iterators 👆

Python Cheatsheet ✅

If you are targeting your first Data Analyst job then this is why you should avoid guided projects The common thing nowadays is "Coffee Sales Analysis" and "Pizza Sales Analysis" I don't see these projects as PROJECTS But as big RED flags We are showing our SKILLS through projects, RIGHT? Then what's WRONG with these projects? Don't think from YOUR side Think from the HIRING team's side These projects have more than a MILLION views on YouTube Even if you consider 50% of this NUMBER Then just IMAGINE how many aspiring Data Analysts would have created this same project Hiring teams see hundreds of resumes and portfolios on a DAILY basis Just imagine how many times they would have seen the SAME titles of projects again and again They would know that these projects are PUBLICLY available for EVERYONE You have simply copied pasted the ENTIRE project from YouTube So now if I want to hire a Data Analyst then how would I JUDGE you or your technical skills? What is the USE of Pizza or Coffee sales analysis projects for MY company? By doing such guided projects, you are involving yourself in a big circle of COMPETITION I repeat, there were more than a MILLION views So please AVOID guided projects at all costs Guided projects are good for your personal PRACTICE and LinkedIn CONTENT But try not to involve them in your PORTFOLIO or RESUME

Step-by-step guide to become a Data Analyst in 2025—📊 1. Learn the Fundamentals: Start with Excel, basic statistics, and data visualization concepts. 2. Pick Up Key Tools & Languages: Master SQL, Python (or R), and data visualization tools like Tableau or Power BI. 3. Get Formal Education or Certification: A bachelor’s degree in a relevant field (like Computer Science, Math, or Economics) helps, but you can also do online courses or certifications in data analytics. 4. Build Hands-on Experience: Work on real-world projects—use Kaggle datasets, internships, or freelance gigs to practice data cleaning, analysis, and visualization. 5. Create a Portfolio: Showcase your projects on GitHub or a personal website. Include dashboards, reports, and code samples. 6. Develop Soft Skills: Focus on communication, problem-solving, teamwork, and attention to detail—these are just as important as technical skills. 7. Apply for Entry-Level Jobs: Look for roles like “Junior Data Analyst” or “Business Analyst.” Tailor your resume to highlight your skills and portfolio. 8. Keep Learning: Stay updated with new tools (like AI-driven analytics), trends, and advanced topics such as machine learning or domain-specific analytics. React ❤️ for more

EssentialSkillsExcel for Data Analysts🚀 1️⃣ Data Cleaning & Transformation Remove Duplicates – Ensure unique records. Find & Replace – Quick data modifications. Text Functions – TRIM, LEN, LEFT, RIGHT, MID, PROPER. Data Validation – Restrict input values. 2️⃣ Data Analysis & Manipulation Sorting & Filtering – Organize and extract key insights. Conditional Formatting – Highlight trends, outliers. Pivot Tables – Summarize large datasets efficiently. Power Query – Automate data transformation. 3️⃣ Essential Formulas & Functions Lookup Functions – VLOOKUP, HLOOKUP, XLOOKUP, INDEX-MATCH. Logical Functions – IF, AND, OR, IFERROR, IFS. Aggregation Functions – SUM, AVERAGE, MIN, MAX, COUNT, COUNTA. Text Functions – CONCATENATE, TEXTJOIN, SUBSTITUTE. 4️⃣ Data Visualization Charts & Graphs – Bar, Line, Pie, Scatter, Histogram. Sparklines – Miniature charts inside cells. Conditional Formatting – Color scales, data bars. Dashboard Creation – Interactive and dynamic reports. 5️⃣ Advanced Excel Techniques Array Formulas – Dynamic calculations with multiple values. Power Pivot & DAX – Advanced data modeling. What-If Analysis – Goal Seek, Scenario Manager. Macros & VBA – Automate repetitive tasks. 6️⃣ Data Import & Export CSV & TXT Files – Import and clean raw data. Power Query – Connect to databases, web sources. Exporting Reports – PDF, CSV, Excel formats. Here you can find some free Excel books & useful resources: https://t.me/excel_data Hope it helps :) #dataanalyst

SQL Data Analytics Roadmap 👆

Data Analyst Interview Questions 👇 1.How to create filters in Power BI? Filters are an integral part of Power BI reports. They are used to slice and dice the data as per the dimensions we want. Filters are created in a couple of ways. Using Slicers: A slicer is a visual under Visualization Pane. This can be added to the design view to filter our reports. When a slicer is added to the design view, it requires a field to be added to it. For example- Slicer can be added for Country fields. Then the data can be filtered based on countries. Using Filter Pane: The Power BI team has added a filter pane to the reports, which is a single space where we can add different fields as filters. And these fields can be added depending on whether you want to filter only one visual(Visual level filter), or all the visuals in the report page(Page level filters), or applicable to all the pages of the report(report level filters) 2.How to sort data in Power BI? Sorting is available in multiple formats. In the data view, a common sorting option of alphabetical order is there. Apart from that, we have the option of Sort by column, where one can sort a column based on another column. The sorting option is available in visuals as well. Sort by ascending and descending option by the fields and measure present in the visual is also available. 3.How to convert pdf to excel? Open the PDF document you want to convert in XLSX format in Acrobat DC. Go to the right pane and click on the “Export PDF” option. Choose spreadsheet as the Export format. Select “Microsoft Excel Workbook.” Now click “Export.” Download the converted file or share it. 4. How to enable macros in excel? Click the file tab and then click “Options.” A dialog box will appear. In the “Excel Options” dialog box, click on the “Trust Center” and then “Trust Center Settings.” Go to the “Macro Settings” and select “enable all macros.” Click OK to apply the macro settings.

📈 Roadmap to Become a Data Analyst — What to Learn in Each Month (6 Months Plan) 🗓️ Month 1: Foundations - Excel (formulas, pivot tables, charts) - Basic Statistics (mean, median, variance, correlation) - Data types & distributions 🗓️ Month 2: SQL Mastery - SELECT, WHERE, GROUP BY, JOINs - Subqueries, CTEs, window functions - Practice on real datasets (e.g. MySQL + Kaggle) 🗓️ Month 3: Python for Analysis - Pandas, NumPy for data manipulation - Matplotlib & Seaborn for visualization - Jupyter Notebooks for presentation 🗓️ Month 4: Dashboarding Tools - Power BI or Tableau - Build interactive dashboards - Learn storytelling with visuals 🗓️ Month 5: Real Projects & Case Studies - Analyze sales, marketing, HR, or finance data - Create full reports with insights & visuals - Document projects for your portfolio 🗓️ Month 6: Interview Prep & Applications - Mock interviews - Revise common questions (SQL, case studies, scenario-based) - Polish resume, LinkedIn, and GitHub React ❤️ for more!