Continuing the #learningpath series
⭐Next skill in #DataScience industry is @MSPowerBI (One of the fastest growing #skills 🚀)
⭐Power BI is one of the leaders in Analytics and BI platforms in @gartner magic quadrant
⭐Step by step learning path for Power BI
A Thread 🧵
1- Getting Started with @MSPowerBI
⭐Power BI Interface
⭐Design flow
⭐Type of data sources
⭐Data Terminology
2.1- Connecting to Data and Intro to Query Editor
⭐Type of Data Sources
⭐Intro to the @MSPowerBI Query Editor
⭐Table Transformations
⭐Text, Number & Date calculations
⭐Index & Conditional Columns
⭐Grouping & Aggregating Data
⭐Pivoting & Unpivoting
2.2- Connecting to Data and Intro to Query Editor
⭐Merging & Appending Queries
⭐Connecting to Folders and import multiple files
⭐Defining Hierarchies & Categories
⭐Query Editing & @MSPowerBI Best Practices
3.1- Building Data Models and Relationships
⭐Intro to Database Normalization
⭐Data ("Fact") Tables vs. Lookup ("Dimension") Tables
⭐Creating @MSPowerBI Table Relationships
⭐"Star" vs. "Snowflake" Schemas
⭐Active vs. Inactive Relationships
⭐Relationship Cardinality
3.2- Building Data Models and Relationships
⭐Connecting Multiple Data Tables
⭐Filtering & Cross-Filtering
⭐Hiding Fields from the @MSPowerBI Report View
⭐Data Modeling & @MSPowerBI best Practices
4.1- Learn Calculated Fields with DAX
⭐Intro to Data Analysis Expressions (DAX)
⭐Calculated Columns vs. Measures
⭐DAX Syntax & Operators
⭐Common Power BI Functions
⭐Basic Date & Time Formulas
⭐Logical & Conditional commands
⭐Text, Math & Stats Functions
4.2- Learn Calculated Fields with DAX
⭐Joining Data with RELATED
⭐CALCULATE, ALL & FILTER Functions
⭐DAX Iterators (SUMX, AVERAGEX)
⭐Quick Measures
⭐Measures v/s custom Columns
⭐Time Intelligence Formulas
⭐DAX & Power BI Best Practices
5. Creating visualizations
⭐Intro to the Power BI Report View
⭐Adding Basic Charts to Power BI Reports
⭐Formatting
⭐Filtering Options
⭐Matrix Visuals
⭐Slicers & Timelines
⭐Cards & KPIs
⭐Power BI Map Visuals (Basic, Fill, ArcGIS)
⭐Tree maps, Lines, Areas & Gauges
6. Other Reporting features and Dashboard Interactions
⭐Editing Report interactions
⭐Adding Drillthrough Filters
⭐Using "What-If" Parameters
⭐Managing & Viewing Roles
⭐Power BI Data Viz Best Practices
⭐Bookmarks
7. Custom Visuals
⭐Using third party Custom Visuals
⭐Installing and using a Custom Visual for Power BI
8. Publishing Reports
⭐Publishing Power BI reports to power BI services
▶️Learning path for data science tools and algorithm
▶️Learn resources for data science
▶️Build Data science Portfolio
▶️Data science resume Building
▶️Apply for data science jobs
Steps to follow👇
Learning Path for data science tools and algorithm
⭐Continuing the #DataScience learning path series and next skill is Python
⭐There always been a debate around R v/s Python
⭐Step by step learning path for Python for data analysis
1⃣ Intro to Python -
⭐Installing and Setting up environment
⭐Install Anaconda and Python
⭐Launch a Jupyter Notebook
⭐Variables and Operators
⭐Booleans and Comparisons
⭐expressions and statements
2⃣ Basics of Python -
⭐Functions, Modules and strings
⭐Lists, Tuples, Sets, and Dictionaries
⭐Installing a Package (Pandas, Scipy, NumPy,Plotly etc.)