Top 5 DAX (Data Analysis Expressions) functions to master Power BI
👇👇
https://www.linkedin.com/posts/sql-analysts_top-5-dax-data-analysis-expressions-functions-activity-7121484515243360256-3x-K

Here is the most awaited post 😄

Free Courses, Projects & Internship for data analytics
👇👇
https://www.linkedin.com/posts/sql-analysts_freecertificates-dataanalysts-python-activity-7123979295600836608-Ut3b

Like this Linkedin post so that it reaches to more data aspirants 😄❤️

319 views but less than 20 likes. Guys, like the linkedin post if its helping you so that linkedin algorithm can send it to more data enthusiasts who can't afford paid courses :)

Thanks guys for the amazing support
180+ likes & 6k+ unique impressions.
You guys are amazing. Will come up with more quality content 😄

Don't waste time in remembering company names & searching their Career pages,

Apply here directly : https://www.linkedin.com/posts/sql-analysts_career-software-design-activity-7126059959988928514-SZjo

Like this Linkedin post so that it reaches to more data aspirants 😄❤️

Free courses to learn Data Science in 2023
👇👇
https://www.linkedin.com/posts/sql-analysts_programming-computerscience-datascience-activity-7126408061472112641-agJe

Like this Linkedin post so that it reaches to more data aspirants 😄❤️

Credit Card Data Analysis Project
👇👇
https://t.iss.one/sqlproject/59

Complete Power BI Book
👇👇
https://www.linkedin.com/posts/sql-analysts_power-bi-book-sqlspecialist-activity-7128010834630369280-AQAR

Like & Share the post with more data aspirants 👍

Unlimited access to data science courses till Nov 20
👇👇
https://www.linkedin.com/posts/sql-analysts_datascience-dataanalytics-activity-7128217526924177408-0DtE

Like for more 👍❤️

Thank you so much guys for reposting content with other data aspirants ❤️

Data Analysis vs Data Science

Data analysis often focuses on interpreting and summarizing existing data, requiring skills like statistical analysis, SQL, and data visualization.
On the other hand, data science involves a broader set of skills, including machine learning, predictive modeling, and advanced programming.

In essence, data analysis is a subset of data science, with data scientists often having a more extensive toolkit for handling complex and unstructured data.

Free Resources to become data analyst -> https://www.linkedin.com/posts/sql-analysts_freecertificates-dataanalysts-python-activity-7113004712412524545-Uw4k

Steps to become data scientist -> https://t.iss.one/learndataanalysis/559

SQL vs Python

SQL is great for managing and querying structured databases, especially when dealing with large datasets. It excels in tasks like filtering, sorting, and aggregating data.

Python, on the other hand, is a versatile programming language used for a broader range of tasks. In the context of data, Python is powerful for data manipulation, analysis, and machine learning. It offers libraries like Pandas for data manipulation, NumPy for numerical operations, and Scikit-Learn for machine learning.

In summary, SQL is essential for efficient database querying, while Python provides a more comprehensive solution for various data-related tasks, making them often used together in data-related workflows.

SQL Practice Questions with Answers -> https://t.iss.one/learndataanalysis/596

Python Roadmap for Data Analysts -> https://t.iss.one/pythonfreebootcamp/207

Free resume guide from Harvard
👇👇
https://www.linkedin.com/posts/sql-analysts_harvard-resume-and-cv-career-guide-activity-7129694373688070144-RS2m

Like and comment on this post so that it reaches more jobseekers 😄👍

Save it for your future reference

Ultimate Resume & Interview Guide
https://www.linkedin.com/posts/sql-analysts_resume-tips-activity-7130056771062153217-ZSsJ?utm_source=share&utm_medium=member_android

Like if it really helps you. It takes a lot of efforts in posting content for you guys ❤️😄

SQL Cheatsheet
👇👇
https://www.linkedin.com/posts/sql-analysts_need-to-learn-sql-but-dont-want-to-spend-activity-7130075632184508417-PKrc?utm_source=share&utm_medium=member_android

Importance of Data Cleaning

https://www.linkedin.com/posts/sql-analysts_datacleaning-dataanalytics-numpy-activity-7131211154634264577-C21z?utm_source=share&utm_medium=member_android

Beginner-friendly Excel Book
👇👇
https://www.linkedin.com/posts/sql-analysts_excel-for-beginners-activity-7131506316677693440-Ip8j

Avoid directly copying YouTube projects onto your resume because if everyone looks the same, recruiters might discard resumes.

Instead, for eg, let's say you are working on a SQL case study, download a dataset from Kaggle (usually a CSV file), set up a Postgre/MySQL database, connect it with the data, and prompt ChatGPT with questions ranging from basic to advanced SQL.

Solve the questions step by step. When using PowerBI, connect to the database and create a compelling dashboard. Don't just upload the dataset; employ DAX queries, statistical functions, and avoid relying solely on drag-and-drop features. Use Formatting section to do creative stuff and add your unique element in the project.

ENJOY LEARNING 👍👍

New Giveaway 500 TB Tutorials + Books + Courses + Trainings + Workshops + Educational Resources
👇👇
https://www.linkedin.com/posts/sql-analysts_python-datascience-aws-activity-7134053938898608128-TCyi?utm_source=share&utm_medium=member_android

Best practices for writing SQL queries:

Join for more: https://t.iss.one/learndataanalysis

1- Write SQL keywords in capital letters.

2- Use table aliases with columns when you are joining multiple tables.

3- Never use select *, always mention list of columns in select clause.

4- Add useful comments wherever you write complex logic. Avoid too many comments.

5- Use joins instead of subqueries when possible for better performance.

6- Create CTEs instead of multiple sub queries , it will make your query easy to read.

7- Join tables using JOIN keywords instead of writing join condition in where clause for better readability.

8- Never use order by in sub queries , It will unnecessary increase runtime.

9- If you know there are no duplicates in 2 tables, use UNION ALL instead of UNION for better performance.

SQL Basics: https://t.iss.one/sqlanalyst/105