u/Tall-Writing5374

So im thinking of studying the fundamentals of data analysis namely: Excel, SQL, and PowerBI (might add python if theres enough time)

so of course i know that even if I study all that for 5 years repeatedly theres still a BIG chance that I wont get a job in data analyst roles, so what im saying is that if the data analyst path doesnt work, what do you guys think is an alternative path (eg. Excel for office jobs) preferably remote work even though its going to be hell

Another question also, is most data analyst roles remote or hybrid?

From what i have learned here, data analysis roles are far too saturated for one to even get accepted and even people with years of experience and degree for that role they would still find it hard to land a job even at the entry-level.

So what more can someone who is still an undergrad with 0 yoe can hope to expect in this industry?

Should i just take another career path to self-study or should i continue this struggle?

If so what careers do you guys think i can study so i can upskill and land a job even in college

So I am planning to learn excel specifically for data analysis, and this is my roadmap which was based off luke barousse but i also added some extra topics (with the help of ai) that was not included in his course which i think could make the roadmap better.

So I just want to ask if the roadmap for excel is good or sufficient enough (sql and powerbi is separate)

Chapter 1: Introduction to Excel

• What is Excel?
• Installing Excel
• UI Walkthrough
• Worksheets & Workbooks
• Ribbon & Menu
• Keyboard Shortcuts

Chapter 2: Excel Basics

• Data Types
• Adding, Deleting & Editing
• Sorting & Filtering

Chapter 3: Formulas & Functions

• Formulas & Functions Intro
• Basic Formulas
• Conditional Functions
• Logical Operators & IS Functions
• Rounding Functions
• Text Functions
• Date Functions
• Math Functions
• Min, Max & Average

Chapter 4: Statistics

• Mean, Median & Mode
• Distributions
• Standard Deviation
• Percentiles
• Statistical Functions

Chapter 5: Lookups

• Lookups Intro
• VLookup & HLookup
• XLookup
• Index Match
• Lookup Practice

Chapter 6: Conditional Formatting

• Highlight Cells Rules
• Top & Bottom Rules
• Bars, Scales & Sets

Chapter 7: Charts & Visualizations

• Bar & Column Charts
• Line & Combo Charts
• Scatter & Bubble Charts
• Pie & Donut Charts
• Map Charts
• Chart Elements, Styles & Axes
• Chart Layouts & Templates
• Visualization Challenge

Chapter 8: Data Cleaning

• Removing Duplicates
• Flash Fill
• Fuzzy Matching
• Standardizing Data
• Handling Missing Data
• Separating & Combining Columns
• Data Validation
• Data Cleaning Practice

Chapter 9: Spreadsheets Advanced

• Tables
• Formatting
• Named Ranges
• Dynamic Arrays
• FILTER, UNIQUE, SORT
• Collaboration

Chapter 10: Pivot Tables

• Pivot Table Intro
• Creating Your First Pivot Table
• Formatting
• Working with Dates
• Calculated Fields
• Sorting & Filtering
• Pivot Charts
• Pivot Tables Advanced
• Practice Challenge

Chapter 11: Advanced Data Analysis

• Analysis Add-ins
• Solver
• Scenario Manager
• Goal Seek
• Data Tables
• Correlation & Regression

Chapter 12: Power Query

• Power Query Intro
• Power Query Editor
• Power Query M Language
• Power Query Advanced

Chapter 13: Power Pivot

• Power Pivot Intro
• Power Pivot DAX
• Data Models

Chapter 14: Macros & Automation

• Recording Macros
• VBA Intro
• Automating Repetitive Tasks

Chapter 15: Storytelling with Data

• Choosing the Right Chart
• Designing for Insight
• Building Dashboards
• Presenting Findings
• Capstone Project

So I am planning to learn excel specifically for data analysis, and this is my roadmap which was based off luke barousse but i also added some extra topics (with the help of ai) that was not included in his course which i think could make the roadmap better.

So I just want to ask if the roadmap for excel is good or sufficient enough (sql and powerbi is separate)

Chapter 1: Introduction to Excel

• What is Excel?
• Installing Excel
• UI Walkthrough
• Worksheets & Workbooks
• Ribbon & Menu
• Keyboard Shortcuts

Chapter 2: Excel Basics

• Data Types
• Adding, Deleting & Editing
• Sorting & Filtering

Chapter 3: Formulas & Functions

• Formulas & Functions Intro
• Basic Formulas
• Conditional Functions
• Logical Operators & IS Functions
• Rounding Functions
• Text Functions
• Date Functions
• Math Functions
• Min, Max & Average

Chapter 4: Statistics

• Mean, Median & Mode
• Distributions
• Standard Deviation
• Percentiles
• Statistical Functions

Chapter 5: Lookups

• Lookups Intro
• VLookup & HLookup
• XLookup
• Index Match
• Lookup Practice

Chapter 6: Conditional Formatting

• Highlight Cells Rules
• Top & Bottom Rules
• Bars, Scales & Sets

Chapter 7: Charts & Visualizations

• Bar & Column Charts
• Line & Combo Charts
• Scatter & Bubble Charts
• Pie & Donut Charts
• Map Charts
• Chart Elements, Styles & Axes
• Chart Layouts & Templates
• Visualization Challenge

Chapter 8: Data Cleaning

• Removing Duplicates
• Flash Fill
• Fuzzy Matching
• Standardizing Data
• Handling Missing Data
• Separating & Combining Columns
• Data Validation
• Data Cleaning Practice

Chapter 9: Spreadsheets Advanced

• Tables
• Formatting
• Named Ranges
• Dynamic Arrays
• FILTER, UNIQUE, SORT
• Collaboration

Chapter 10: Pivot Tables

• Pivot Table Intro
• Creating Your First Pivot Table
• Formatting
• Working with Dates
• Calculated Fields
• Sorting & Filtering
• Pivot Charts
• Pivot Tables Advanced
• Practice Challenge

Chapter 11: Advanced Data Analysis

• Analysis Add-ins
• Solver
• Scenario Manager
• Goal Seek
• Data Tables
• Correlation & Regression

Chapter 12: Power Query

• Power Query Intro
• Power Query Editor
• Power Query M Language
• Power Query Advanced

Chapter 13: Power Pivot

• Power Pivot Intro
• Power Pivot DAX
• Data Models

Chapter 14: Macros & Automation

• Recording Macros
• VBA Intro
• Automating Repetitive Tasks

Chapter 15: Storytelling with Data

• Choosing the Right Chart
• Designing for Insight
• Building Dashboards
• Presenting Findings
• Capstone Project