Many people pay too much to learn Power BI, but my mission is to break down barriers. I have shared complete learning series to learn Power BI from scratch.

Here are the links to the Power BI series

Complete Power BI Topics for Data Analyst: https://t.me/sqlspecialist/588

Part-1: https://t.me/sqlspecialist/589

Part-2: https://t.me/sqlspecialist/590

Part-3: https://t.me/sqlspecialist/592

Part-4: https://t.me/sqlspecialist/595

Part-5: https://t.me/sqlspecialist/597

Part-6: https://t.me/sqlspecialist/600

Part-7: https://t.me/sqlspecialist/603

Part-8: https://t.me/sqlspecialist/604

Part-9: https://t.me/sqlspecialist/605

Part-10: https://t.me/sqlspecialist/606

Part-11: https://t.me/sqlspecialist/609

Part-12:
https://t.me/sqlspecialist/610

Part-13: https://t.me/sqlspecialist/613

Part-14: https://t.me/sqlspecialist/614

More Power BI Resources: https://t.me/PowerBI_analyst

I'll continue with learning series on Excel & Tableau. I am also planning to start with Interview Preparation Series as have already covered essential concepts of Python, SQL & Power BI in detail.

Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.

Hope it helps :)

Complete Roadmap to learn Power BI in 2024 👇👇
https://www.linkedin.com/posts/sql-analysts_complete-roadmap-to-learn-power-bi-activity-7189616719936573441-rRgu?utm_source=share&utm_medium=member_android

Tableau Roadmap 👇👇
https://www.linkedin.com/posts/sql-analysts_complete-roadmap-to-learn-tableau-in-2024-activity-7189976586002022400-9gxo?utm_source=share&utm_medium=member_android

Learn Power BI 👇👇
https://powerbi.microsoft.com/en-us/learning/

Don’t forget to share your response by reacting to this message ❣️🥰

Useful tips to select Chart Type

👉 If you have categorical data,then either use a bar chart if you have more than 5 categories or a pie chart for less than 5 categories.

👉 If you have nominal data, use bar charts ; histograms if your data is discrete,; line/ area charts if it is continuous.

👉 If you want to show the relationship between values in your dataset, use a scatter plot, bubble chart, or line charts.

👉 If you want to compare values, use a pie chart — for relative comparison — or bar charts — for precise comparison.

👉 If you want to compare volumes, use an area chart or a bubble chart.

👉 If you want to show trends and patterns in your data, use a line chart, bar chart, or scatter plot.

Ways to improve the performance of Tableau

👉🏻 Use an Extract to make workbooks run faster.
👉🏻 Reduce the number of marks on the view to avoid information overload.
👉🏻 Hide unused fields.
👉🏻 Use Context filters.
👉🏻 Use indexing in tables and use the same fields for filtering.
👉🏻 Remove unnecessary calculations and sheets.

Best Practices while creating Power bi dashboards
https://www.linkedin.com/posts/sql-analysts_best-practices-to-remember-while-creating-activity-7193465180935094272-dhx1?utm_source=share&utm_medium=member_android

How does deployment cycle in Power BI works? (Asked by Prawin)

1. Development: In this phase, reports and dashboards are created using Power BI Desktop. Data is imported, transformed, and modeled to create visualizations and insights.

2. Testing: Once the reports and dashboards are developed, they need to be tested to ensure they are accurate and meet the requirements of the business users. This can involve testing data connections, calculations, and visualizations.

3. Publishing: After testing is complete, the reports and dashboards are published to the Power BI Service. This allows users to access and interact with the reports online.

4. Sharing: Reports and dashboards can be shared with other users within the organization by creating a workspace and granting access to specific users or groups.

5. Refreshing: Data in the reports needs to be kept up-to-date, so scheduled refreshes can be set up to automatically update the data in the reports on a regular basis.

6. Monitoring: It's important to monitor the performance of the reports and dashboards to ensure they are meeting the needs of the users. This can involve tracking usage metrics, identifying any issues, and making improvements as needed.

7. Iteration: As business requirements change or new data sources become available, the reports and dashboards may need to be updated or revised. This iterative process ensures that the reports continue to provide value to the organization.

Best practices to follow while creating Tableau dashboards
👇👇
https://www.linkedin.com/posts/sql-analysts_learn-tableau-activity-7195275749245784064-9TNf?utm_source=share&utm_medium=member_android

Some advanced Data Visualization concepts you should know to enhance the explanatory power of your graphs:

1. Colour Coding
2. Line Styles
3. Conditional Formatting
4. Subplots
5. Interactive Elements

Quick Power BI Dax Revision

1. Measures: Measures in DAX are calculations that are used in Power BI to perform aggregations, calculations, and comparisons on data. They are defined using the DEFINE MEASURE or CALCULATE functions.

2. Calculated Columns: Calculated columns are columns that are created in a table by using DAX expressions. They are calculated row by row when the data is loaded into the model.

3. DAX Functions: DAX provides a wide range of functions for data manipulation and calculation. Some common functions include SUM, AVERAGE, COUNT, FILTER, CALCULATE, RELATED, ALL, ALLEXCEPT, and many more.

4. Context: DAX calculations are performed within a context, which can be row context or filter context. Understanding how context works is crucial for writing accurate DAX expressions.

5. Relationships: Power BI data models are built on relationships between tables. DAX expressions can leverage these relationships to perform calculations across related tables.

6. Time Intelligence Functions: DAX includes a set of time intelligence functions that enable you to perform calculations based on dates and time periods. Examples include TOTALYTD, SAMEPERIODLASTYEAR, DATESBETWEEN, etc.

7. Variables: DAX allows you to declare and use variables within expressions to improve readability and performance of complex calculations.

8. Aggregation Functions: DAX provides aggregation functions like SUMX, AVERAGEX, COUNTX that allow you to iterate over a table and perform aggregations based on specified conditions.

9. Logical Functions: DAX includes logical functions such as IF, AND, OR, SWITCH that help in implementing conditional logic within calculations.

10. Error Handling: DAX provides functions like ISBLANK, IFERROR, BLANK, etc., for handling errors and missing data in calculations.

Added one amazing book called data visualisation made easy with these resources. Give it a read whenever you get time ❤️

📘 Free Power BI Course by Microsoft

https://learn.microsoft.com/en-us/power-bi/

Hope you'll like it

Like this post if you need more resources like this 👍❤️

If you're looking to build a career in Data Analytics but feel unsure about where to start, this post is for you.

It's important to know that you don't need to spend money on expensive courses to succeed in this field.

Many posts you see on LinkedIn promoting paid courses are often shared by individuals who are either trying to sell their own products or are being compensated to endorse these courses.

Through this post, I will share with you everything you need to start your data journey absolutely free.

🔗 Source

Hope it helps :)

HOW TO LEARN POWER BI IN 2024 👇👇

🔺Get Familiar with Basics: Start by understanding the basics of Power BI, such as data sources, data modeling, and visualization concepts.

🔺Install Power BI Desktop: Download and install Power BI Desktop, the free version of Power BI, to begin creating reports and dashboards on your local machine.

🔺Explore Sample Data: Use sample datasets provided by Power BI to practice creating visualizations and getting comfortable with the interface.

🔺Learn Data Loading: Understand how to import data into Power BI from various sources, including Excel, databases, and online services.

🔺Data Transformation: Learn the process of cleaning and transforming data using Power Query to ensure it's suitable for analysis.

🔺Data Modeling: Grasp the fundamentals of data modeling, including relationships between tables, creating calculated columns, and measures.

🔺Create Visualizations: Practice creating different types of visualizations like charts, tables, and maps to represent your data effectively.

🔺Master DAX (Data Analysis Expressions): DAX is the formula language used in Power BI. Learn how to create calculated columns, measures, and calculated tables using DAX.

🔺Build Dashboards: Combine visualizations into interactive dashboards to convey insights effectively. Understand how to use filters and slicers.

🔺Publish to Power BI Service: Explore Power BI Service, where you can publish your reports and share them with others. Learn about collaboration features.

🔺Explore Advanced Features: Dive into advanced features like Power BI Apps, Power Automate integration, and Power BI Embedded for more sophisticated applications.

🔺Stay Updated: As Power BI is regularly updated, stay informed about new features and improvements. Join online communities or forums to connect with other Power BI users and learn from their experiences.

👀🧠Remember, consistent practice and real-world projects will enhance your skills. Utilize online resources, tutorials, and documentation provided by Microsoft to deepen your understanding.

❌ Power BI alone won’t make you Data Analyst
❌ Power BI cannot get you a 18 LPA job offer
❌ Power BI cannot be mastered in 2 days
❌ Power BI is not just colorful dashboard
❌ Power BI is not simple “drag and drop”
❌ Power BI isn’t for Data Analysts only

But here’s what Power BI can do:

✔️ Power BI can save your reporting time
✔️ Power BI keeps your confidential data safe
✔️ Power BI helps you say bye to Pivot Tables
✔️ Power BI makes your report easy to consume
✔️ Power BI can update your dashboard with a single click
✔️ Power BI handles heavy data without testing your patience
✔️ Power BI is the next level for people whose work depends on Excel


I can go on and on, but you get the point.

Wrong expectations -> Wrong results
Right expectations -> Amazing results