Priyanka SG’s Post

Must Study: These are the important Questions for Data Analyst(Beginners) SQL Server 1. Explain the difference between UNION and UNION ALL. 2. What is a subquery, and how is it different from a join? 3. How do you handle transactions in SQL Server? Excel 1. What are the different types of charts available in Excel, and how do you choose the right one? 2. How do you use Excel’s IF, AND, OR, and NOT functions for logical operations? 3. How do you create and manage named ranges in Excel? Power BI 1. How do you create and manage relationships between tables in Power BI? 2. What is the purpose of the Query Editor in Power BI, and how do you use it for data transformation? 3. How do you implement bookmarks and buttons in Power BI for navigation and interactivity? Python 1. What are Python's built-in data structures? 2. How do you handle missing data in a dataset using Python? 3. What are Python decorators, and how do you use them? Data Visualization 1. What are the key principles of effective data visualization? 2. How do you choose the right type of visualization for your data? 3. What are common pitfalls to avoid in data visualization? #Excel #Sql #PowerBI #Python #DataAnalyst

Must Study: These are the important Questions for Data Analyst(Beginners) SQL Server 1. Explain the difference between UNION and UNION ALL. 2. What is a subquery, and how is it different from a join? 3. How do you handle transactions in SQL Server? Excel 1. What are the different types of charts available in Excel, and how do you choose the right one? 2. How do you use Excel’s IF, AND, OR, and NOT functions for logical operations? 3. How do you create and manage named ranges in Excel? Power BI 1. How do you create and manage relationships between tables in Power BI? 2. What is the purpose of the Query Editor in Power BI, and how do you use it for data transformation? 3. How do you implement bookmarks and buttons in Power BI for navigation and interactivity? Python 1. What are Python's built-in data structures? 2. How do you handle missing data in a dataset using Python? 3. What are Python decorators, and how do you use them? Data Visualization 1. What are the key principles of effective data visualization? 2. How do you choose the right type of visualization for your data? 3. What are common pitfalls to avoid in data visualization? #SQL #DataAnalytics

Must Study: These are the important Questions for Data Analyst ✅ SQL 1. How do you handle NULL values in SQL queries, and why is it important? 2. What is the difference between INNER JOIN and OUTER JOIN, and when would you use each? 3. How do you implement transaction control in SQL Server? Excel 1. How do you use pivot tables to analyze large datasets in Excel? 2. What are Excel's built-in functions for statistical analysis, and how do you use them? 3. How do you create interactive dashboards in Excel? Power BI 1. How do you optimize Power BI reports for performance? 2. What is the role of DAX (Data Analysis Expressions) in Power BI, and how do you use it? 3. How do you handle real-time data streaming in Power BI? Python 1. How do you use Pandas for data manipulation, and what are some advanced features? 2. How do you implement machine learning models in Python, from data preparation to deployment? 3. What are the best practices for handling large datasets in Python? Data Visualization 1. How do you choose the right visualization technique for different types of data? 2. What is the importance of color theory in data visualization? 3. How do you use tools like Tableau or Power BI for advanced data storytelling? #sql #excel #dataanalyst #pythom #powerbi

Must Study:- These are the important Questions for Data Analyst 3.0 Advanced SQL 1. How do you optimize SQL queries for performance? 2. What are window functions, and how are they used in SQL Server? 3. How do you handle data normalization and denormalization in SQL? Excel Advanced 1. How do you use Power Query for data transformation in Excel? 2. Explain how to create and use dynamic arrays in Excel. 3. How do you implement advanced conditional formatting rules in Excel? Power BI 1. How do you create and manage relationships between tables in Power BI? 2. What are the different types of Power BI visuals and when should you use each? 3. How do you implement row-level security in Power BI reports? Python 1. How do you perform web scraping using Python? 2. What are the key libraries for machine learning in Python, and how are they used? 3. How do you handle missing data and outliers in Python? Data Visualization 1. How do you design visualizations that cater to different audiences? 2. What are the common pitfalls in data visualization, and how do you avoid them? 3. How do you integrate interactive elements in data visualizations? Soft Skills 1. How do you prioritize tasks and manage deadlines in a data project? 2. What strategies do you use to build strong relationships with stakeholders? 3. How do you approach problem-solving and decision-making in a data-driven environment? Follow more for Priyanka SG #SQL #EXCEL #POWERBI #PYTHON #DATAANALYST

Top 5 Tools to Master to be called a data analytics expert? Choosing the right tool depends on the type of analytics you need to perform: For clear and easy-to-understand data presentations, choose Tableau or Power BI. For in-depth data analysis and building complex models, use Python. To access and analyze data stored in relational databases, use SQL. For smaller datasets and basic tasks, Excel can be sufficient. #risk #consulting

📊 3 Key Skills Every Aspiring Data Analyst Should Focus On: 1️⃣ SQL Mastery : SQL is the backbone of data querying. Whether it's retrieving, updating, or analyzing data, SQL lets you interact with databases efficiently. Start with the basics, then dive into advanced queries like JOINS, subqueries, and window functions. 2️⃣ Data Visualization : Turning raw data into meaningful visuals is critical for communicating insights. Tools like Power BI or Tableau help create intuitive, interactive dashboards that bring data stories to life. 3️⃣ Python for Data: From data cleaning to machine learning, Python has a wide range of libraries like Pandas, NumPy, and Matplotlib. It’s a powerful tool to automate tasks and deepen your analysis. 🌟 Focus on these skills to build a strong foundation and thrive in the data world! #DataAnalytics #LearningWithData #DataSkills #SQL #PowerBI #Python

Becoming a Data Analyst doesn't need to be more complicated than: 1. Excel/Stats 2. SQL 3. Tableau/ PowerBI -> Build dashboards 4. Python/R -> Analyse + Visualise Data 5. Using the above, build Portfolio projects (From data cleaning → Tell the story → Recommendation & Actions) 6. Improve each one step at a time.

Breaking into Data Analysis can be very confusing in 2024! Should I learn SQL or NoSQL? Tableau or Power BI? Excel or Google Sheets? Python or R? Fundamental principles are more important than tools: Understanding data cleaning and preprocessing is more important than SQL vs NoSQL. Understanding data visualization concepts is more important than Tableau vs Power BI. Understanding statistical analysis is more important than Excel vs R. Understanding programming for data manipulation is more important than Python vs R. Knowing these will allow you to pick up new emerging tools easily. Stick to fundamentals first. #SQL #interviewprep #databases #Python #DataAnalysis

Becoming a Data Analyst doesn't need to be more complicated than: 1. Excel/Stats 2. SQL 3. Tableau/ PowerBI -> Build dashboards 4. Python/R -> Analyse + Visualise Data 5. Using the above, build portfolio projects (from data cleaning → Tell the story → Recommendation & Actions).  6. Improve each one step at a time.

Want better insights from your data? Look no further! Master data analytics with these top 5 tools recommended by users: 1. Tableau - for creating visually appealing dashboards. 2. Python Software Foundation - for advanced data manipulation and analysis. 3. Oracle MySQL - for querying databases efficiently. 4. Excel - for basic data manipulation and visualization. 5. Power BI - for creating interactive reports. With these tools in your arsenal, unlock powerful insights and make better decisions based on data. Start mastering data analytics today! #dataanalytics #DataAnalyticsTools #python #tableau #SQL #Excel #PowerBI #datascience #plusyourcareergrowth #eduplusnow