Master Power BI with this Cheat Sheet🔥

If you're preparing for a Power BI interview, this cheat sheet covers the key concepts and DAX commands you'll need. Bookmark it for last-minute revision!

📝 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗕𝗮𝘀𝗶𝗰𝘀:

DAX Functions:

- SUMX: Sum of values based on a condition.
- FILTER: Filter data based on a given condition.
- RELATED: Retrieve a related column from another table.
- CALCULATE: Perform dynamic calculations.
- EARLIER: Access a column from a higher context.
- CROSSJOIN: Create a Cartesian product of two tables.
- UNION: Combine the results from multiple tables.
- RANKX: Rank data within a column.
- DISTINCT: Filter unique rows.

Data Modeling:

- Relationships: Create, manage, and modify relationships.
- Hierarchies: Build time-based hierarchies (e.g., Date, Month, Year).
- Calculated Columns: Create calculated columns to extend data.
- Measures: Write powerful measures to analyze data effectively.

Data Visualization:

- Charts: Bar charts, line charts, pie charts, and more.
- Table & Matrix: Display tabular data and matrix visuals.
- Slicers: Create interactive filters.
- Tooltips: Enhance visual interactivity with tooltips.
- Map: Display geographical data effectively.

✨ 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗧𝗶𝗽𝘀:

✅ Use DAX for efficient data analysis.

✅ Optimize data models for performance.

✅ Utilize drill-through and drill-down for deeper insights.

✅ Leverage bookmarks for enhanced navigation.

✅ Annotate your reports with comments for clarity.

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Some important questions to crack data science interview

Q. Describe how Gradient Boosting works.

A. Gradient boosting is a type of machine learning boosting. It relies on the intuition that the best possible next model, when combined with previous models, minimizes the overall prediction error. If a small change in the prediction for a case causes no change in error, then next target outcome of the case is zero. Gradient boosting produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees.


Q. Describe the decision tree model.

A. Decision Trees are a type of Supervised Machine Learning where the data is continuously split according to a certain parameter. The leaves are the decisions or the final outcomes. A decision tree is a machine learning algorithm that partitions the data into subsets.


Q. What is a neural network?

A. Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input. They, also known as Artificial Neural Networks, are the subset of Deep Learning.


Q. Explain the Bias-Variance Tradeoff

A. The bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters.


Q. What’s the difference between L1 and L2 regularization?

A. The main intuitive difference between the L1 and L2 regularization is that L1 regularization tries to estimate the median of the data while the L2 regularization tries to estimate the mean of the data to avoid overfitting. That value will also be the median of the data distribution mathematically.

ENJOY LEARNING 👍👍

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Here is an A-Z list of essential programming terms:

1. Array: A data structure that stores a collection of elements of the same type in contiguous memory locations.

2. Boolean: A data type that represents true or false values.

3. Conditional Statement: A statement that executes different code based on a condition.

4. Debugging: The process of identifying and fixing errors or bugs in a program.

5. Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions.

6. Function: A block of code that performs a specific task and can be called multiple times in a program.

7. GUI (Graphical User Interface): A visual way for users to interact with a computer program using graphical elements like windows, buttons, and menus.

8. HTML (Hypertext Markup Language): The standard markup language used to create web pages.

9. Integer: A data type that represents whole numbers without any fractional part.

10. JSON (JavaScript Object Notation): A lightweight data interchange format commonly used for transmitting data between a server and a web application.

11. Loop: A programming construct that allows repeating a block of code multiple times.

12. Method: A function that is associated with an object in object-oriented programming.

13. Null: A special value that represents the absence of a value.

14. Object-Oriented Programming (OOP): A programming paradigm based on the concept of "objects" that encapsulate data and behavior.

15. Pointer: A variable that stores the memory address of another variable.

16. Queue: A data structure that follows the First-In-First-Out (FIFO) principle.

17. Recursion: A programming technique where a function calls itself to solve a problem.

18. String: A data type that represents a sequence of characters.

19. Tuple: An ordered collection of elements, similar to an array but immutable.

20. Variable: A named storage location in memory that holds a value.

21. While Loop: A loop that repeatedly executes a block of code as long as a specified condition is true.

Best Programming Resources: https://topmate.io/coding/898340

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🏟 Here is a complete roadmap to learn Data Structures and Algorithms (DSA) 🏟


1. Basics of Programming: Start by learning the basics of a programming language like Python, Java, or C++. Understand concepts like variables, loops, functions, and arrays.

2. Data Structures: Study fundamental data structures like arrays, linked lists, stacks, queues, trees, graphs, and hash tables. Understand the operations that can be performed on these data structures and their time complexities.

3. Algorithms: Learn common algorithms like searching, sorting, recursion, dynamic programming, greedy algorithms, and divide and conquer. Understand how these algorithms work and their time complexities.

4. Problem Solving: Practice solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Start with easy problems and gradually move to medium and hard problems.

5. Complexity Analysis: Learn how to analyze the time and space complexity of algorithms. Understand Big O notation and how to calculate the complexity of different algorithms.

6. Advanced Data Structures: Study advanced data structures like AVL trees, B-trees, tries, segment trees, and fenwick trees. Understand when and how to use these data structures in problem-solving.

7. Graph Algorithms: Learn graph traversal algorithms like BFS and DFS. Study algorithms like Dijkstra's algorithm, Bellman-Ford algorithm, and Floyd-Warshall algorithm for shortest path problems.

8. Dynamic Programming: Master dynamic programming techniques for solving complex problems efficiently. Practice solving dynamic programming problems to build your skills.

9. Practice and Review: Regularly practice coding problems and review your solutions. Analyze your mistakes and learn from them to improve your problem-solving skills.

10. Mock Interviews: Prepare for technical interviews by participating in mock interviews and solving interview-style coding problems. Practice explaining your thought process and reasoning behind your solutions.

Best DSA RESOURCES: https://topmate.io/coding/886874

All the best 👍👍

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Goldman Sachs senior data analyst interview asked questions

SQL

1 find avg of salaries department wise from table
2 Write a SQL query to see employee name and manager name using a self-join on 'employees' table with columns 'emp_id', 'name', and 'manager_id'.
3 newest joinee for every department (solved using lead lag)

POWER BI

1. What does Filter context in DAX mean?
2. Explain how to implement Row-Level Security (RLS) in Power BI.
3. Describe different types of filters in Power BI.
4. Explain the difference between 'ALL' and 'ALLSELECTED' in DAX.
5. How do you calculate the total sales for a specific product using DAX?

PYTHON

1. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
2. Find unique values in a list of assorted numbers and print the count of how many times each value is repeated.
3. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.

Hope this helps you 😊

For a data analytics interview, focusing on key SQL topics can be crucial. Here's a list of last-minute SQL topics to revise:

1. SQL Basics:
• SELECT statements: Syntax, SELECT DISTINCT
• WHERE clause: Conditions and operators (>, <, =, LIKE, IN, BETWEEN)
• ORDER BY clause: Sorting results
• LIMIT clause: Limiting the number of rows returned

2. Joins:
• INNER JOIN
• LEFT (OUTER) JOIN
• RIGHT (OUTER) JOIN
• FULL (OUTER) JOIN
• CROSS JOIN
• Understanding join conditions and scenarios for each type of join

3. Aggregation and Grouping:
• GROUP BY clause
• HAVING clause: Filtering grouped results
• Aggregate functions: COUNT, SUM, AVG, MIN, MAX

4. Subqueries:
• Nested subqueries: Using subqueries in SELECT, FROM, WHERE, and HAVING clauses
• Correlated subqueries

5. Common Table Expressions (CTEs):
• Syntax and use cases for CTEs (WITH clause)

6. Window Functions:
• ROW_NUMBER()
• RANK()
• DENSE_RANK()
• LEAD() and LAG()
• PARTITION BY clause

7. Data Manipulation:
• INSERT, UPDATE, DELETE statements
• Understanding transaction control with COMMIT and ROLLBACK

8. Data Definition:
• CREATE TABLE
• ALTER TABLE
• DROP TABLE
• Constraints: PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL

9. Indexing:
• Purpose and types of indexes
• How indexing affects query performance

10. Performance Optimization:
• Understanding query execution plans
• Identifying and resolving common performance issues

11. SQL Functions:
• String functions: CONCAT, SUBSTRING, LENGTH
• Date functions: DATEADD, DATEDIFF, GETDATE
• Mathematical functions: ROUND, CEILING, FLOOR

12. Stored Procedures and Triggers:
• Basics of writing and using stored procedures
• Basics of writing and using triggers

13. ETL (Extract, Transform, Load):
• Understanding the process and SQL's role in ETL operations

14. Advanced Topics (if time permits):
• Understanding complex data types (JSON, XML)
• Working with large datasets and big data considerations

Hope it helps :)

Top 9 Http Methods-

GET 🧐 - Retrieve data from a resource.
HEAD 🎧 - Retrieve the headers of a resource.
POST 📮 - Submit data to a resource.
PUT 📥 - Update an existing resource or create a new resource.
DELETE 🗑️ - Remove a resource.
CONNECT 🔗 - Establish a network connection for a resource.
OPTIONS ⚙️ - Describe communication options for the target resource.
TRACE 🕵️‍♂️ - Retrieve a diagnostic trace of the request.
PATCH 🩹 - Apply a partial update to a resource.

How to become a Pro Web Developer? ⚡

Step 1: Learn HTML & CSS
Step 2: Build projects
Step 3: Learn Git
Step 4: Learn CSS Frameworks
Step 5: Build projects
Step 6: Learn JavaScript
Step 7: Build projects
Step 8: Learn frontend framework
Step 9: Build projects
Step 10: Build some more projects
Step 10: Learn NodeJS, APIs and Databases
Step 11: Build projects

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Spend more time building projects
Good luck 🤞

The most popular programming languages:

1. Python
2. TypeScript
3. JavaScript
4. C#
5. HTML
6. Rust
7. C++
8. C
9. Go
10. Lua
11. Kotlin
12. Java
13. Swift
14. Jupyter Notebook
15. Shell
16. CSS
17. GDScript
18. Solidity
19. Vue
20. PHP
21. Dart
22. Ruby
23. Objective-C
24. PowerShell
25. Scala

According to the Latest GitHub Repositories

Top 10 CSS Interview Questions

1. What is CSS and what are its key features?
CSS (Cascading Style Sheets) is a stylesheet language used to describe the presentation of a document written in HTML or XML. Its key features include controlling layout, styling text, setting colors, spacing, and more, allowing for a separation of content and design for better maintainability and flexibility.

2. Explain the difference between inline, internal, and external CSS.
- Inline CSS is applied directly within an HTML element using the style attribute.
- Internal CSS is defined within a <style> tag inside the <head> section of an HTML document.
- External CSS is linked to an HTML document via the <link> tag and is written in a separate .css file.

3. What is the CSS box model and what are its components?
The CSS box model describes the rectangular boxes generated for elements in the document tree and consists of four components:
- Content: The actual content of the element.
- Padding: The space between the content and the border.
- Border: The edge surrounding the padding.
- Margin: The space outside the border that separates the element from others.

4. How do you center a block element horizontally using CSS?
To center a block element horizontally, you can use the margin: auto; property. For example:

.center {
  width: 50%;
  margin: auto;
}

5. What are CSS selectors and what are the different types?
CSS selectors are patterns used to select elements to apply styles. The different types include:
- Universal selector (*)
- Element selector (element)
- Class selector (.class)
- ID selector (#id)
- Attribute selector ([attribute])
- Pseudo-class selector (:pseudo-class)
- Pseudo-element selector (::pseudo-element)

6. Explain the difference between absolute, relative, fixed, and sticky positioning in CSS.
- relative: The element is positioned relative to its normal position.
- absolute: The element is positioned relative to its nearest positioned ancestor or the initial containing block if none exists.
- fixed: The element is positioned relative to the viewport and does not move when the page is scrolled.
- sticky: The element is treated as relative until a given offset position is met in the viewport, then it behaves as fixed.

7. What is Flexbox and how is it used in CSS?
Flexbox (Flexible Box Layout) is a layout model that allows for more efficient arrangement of elements within a container. It is used to align and distribute space among items in a container, even when their size is unknown or dynamic. Flexbox is enabled by setting display: flex; on a container element.

8. How do you create a responsive design in CSS?
Responsive design can be achieved using media queries, flexible grid layouts, and relative units like percentages, em, and rem. Media queries adjust styles based on the viewport's width, height, and other characteristics. For example:

@media (max-width: 600px) {
  .container {
    width: 100%;
  }
}

9. What are CSS preprocessors and name a few popular ones.
CSS preprocessors extend CSS with variables, nested rules, and functions, making it more powerful and easier to maintain. Popular CSS preprocessors include:
- Sass (Syntactically Awesome Style Sheets)
- LESS (Leaner Style Sheets)
- Stylus

10. How do you implement CSS animations?
CSS animations are implemented using the @keyframes rule to define the animation and the animation property to apply it to an element. For example:

@keyframes example {
  from {background-color: red;}
  to {background-color: yellow;}
}

.element {
  animation: example 5s infinite;
}

Web Development Best Resources: https://topmate.io/coding/930165

ENJOY LEARNING 👍👍

✅ Coding A-Z: Your Essential Guide 💻 ✨

🅰️ Algorithm: A step-by-step procedure for solving a problem. The backbone of every program.

🅱️ Boolean: A data type with only two possible values: true or false. The foundation of logic in code.

©️ Class: A blueprint for creating objects, encapsulating data and methods. Central to object-oriented programming.

🅳 Data Structure: A way of organizing and storing data for efficient access and modification (e.g., arrays, linked lists, trees).

🅴 Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions (handle them!).

🅵 Function: A block of organized, reusable code that performs a specific task. A building block of modular code.

🅶 Git: A distributed version control system for tracking changes in source code during software development. Essential for collaboration.

🅷 HTTP (Hypertext Transfer Protocol): The foundation of data communication on the World Wide Web.

🅸 IDE (Integrated Development Environment): A software application that provides comprehensive facilities to computer programmers for software development (e.g., VS Code, IntelliJ).

🅹 JSON (JavaScript Object Notation): A lightweight data-interchange format that is easy for humans to read and write and easy for machines to parse and generate.

🅺 Keyword: A reserved word in a programming language that has a special meaning and cannot be used as an identifier.

🅻 Loop: A sequence of instructions that is continually repeated until a certain condition is reached (e.g., for loop, while loop).

🅼 Method: A function that is associated with an object. They define the behavior of objects.

🅽 Null: Represents the absence of a value or a non-existent object pointer.

🅾️ Object: A fundamental concept in object-oriented programming, it is an instance of a class, containing data (attributes) and code (methods).

🅿️ Polymorphism: The ability of different classes to respond to the same method call in their own specific way.

🆀 Query: A request for data from a database.

🆁 Recursion: A function that calls itself to solve a smaller instance of the same problem. Useful for problems with self-similar substructures.

🆂 String: A sequence of characters, used to represent text.

🆃 Thread: A small unit of CPU execution, that can be executed concurrently with other units of the same program.

🆄 Unicode: A character encoding standard that provides a unique number for every character, regardless of the platform, program, or language.

🆅 Variable: A named storage location in the computer's memory that can hold a value.

🆆 While Loop: A control flow statement that allows code to be executed repeatedly based on a given boolean condition.

🆇 XML (Extensible Markup Language): A markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable.

🆈 YAML (YAML Ain't Markup Language): A human-readable data serialization language often used for configuration files and in applications where data is being stored or transmitted.

🆉 Zero-Based Indexing: A way of indexing an array where the first element has an index of zero.

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How to Learn Java in 2025

1. Set Clear Goals:
   - Define your learning objectives. Do you want to build web applications, mobile apps, or work on enterprise-level software?


2. Choose a Structured Learning Path:
   - Follow a structured learning path that covers the fundamentals of Java, object-oriented programming principles, and essential libraries.


3. Start with the Basics:
   - Begin with the core concepts of Java, such as variables, data types, operators, and control flow statements.


4. Master Object-Oriented Programming:
   - Learn about classes, objects, inheritance, polymorphism, and encapsulation.


5. Explore Java Libraries:
   - Familiarize yourself with commonly used Java libraries, such as those for input/output, networking, and data structures.


6. Practice Regularly:
   - Write code regularly to reinforce your understanding and identify areas where you need more practice.


7. Leverage Online Resources:
   - Utilize online courses, tutorials, and documentation to supplement your learning.


8. Join a Coding Community:
   - Engage with online coding communities and forums to ask questions, share knowledge, and collaborate on projects.


9. Build Projects:
   - Create simple projects to apply your skills and gain practical experience.


10. Stay Updated with Java Releases:
    - Keep up with the latest Java releases and updates to ensure your knowledge remains current.


11. Explore Frameworks and Tools:
    - Learn about popular Java frameworks and tools, such as Spring Boot, Maven, and IntelliJ IDEA.


12. Contribute to Open Source Projects:
    - Contribute to open source Java projects to gain real-world experience and showcase your skills.


13. Seek Feedback and Mentoring:
    - Seek feedback from experienced Java developers and consider mentorship opportunities to accelerate your learning.


14. Prepare for Certifications:
    - Consider pursuing Java certifications, such as the Oracle Certified Java Programmer (OCJP), to validate your skills.


15. Network with Java Developers:
    - Attend Java meetups, conferences, and online events to connect with other Java developers and learn from their experiences.

👨‍💻 Preparing for a Coding Interview? Here’s What You Need to Know! 💻⚙️

Whether it’s a tech giant or a startup, coding interviews test problem-solving and clarity.

🔹 Basics:
→ Master data structures: arrays, strings, linked lists, stacks, queues.
→ Practice basic algorithms: sorting, searching, recursion.

🔹 Intermediate:
→ Focus on trees, graphs, hashmaps, dynamic programming, and sliding window techniques.
→ Learn time & space complexity analysis.

🔹 Advanced:
→ Tackle system design (for senior roles), bit manipulation, multi-threading basics, and low-level optimizations.
→ Work on real coding platforms (LeetCode, HackerRank, Codeforces).

🡲 Quick Tip: Practice explaining your solution out loud. Communication is as important as the code!

👍 Tap ❤️ if you found this helpful!

Top 7 Must-Prepare Topics for Coding Interviews (2025 Edition)

✅ Arrays & Strings – Master problems on rotation, sliding window, two pointers, etc.
✅ Linked Lists – Practice reversal, cycle detection, and merging lists
✅ Hashing & Maps – Use hash tables for fast lookups and frequency-based problems
✅ Recursion & Backtracking – Solve problems like permutations, subsets, and Sudoku
✅ Dynamic Programming – Understand memoization, tabulation, and classic patterns
✅ Trees & Graphs – Cover traversal (BFS/DFS), shortest paths, and tree operations
✅ Stacks & Queues – Solve problems involving monotonic stacks, parentheses, and sliding windows

These are the essentials to crack FAANG-level interviews or product-based companies.

React with ❤️ for detailed explanation on each topic