We began with the bigger picture to be an analyst but let us break it down into manageable chunks now.

Some recommend you start with statistics but let me just say start wherever you are comfortable. If you find a topic overwhelming take a break or rest then come back to the topic. Somehow you gain better insights on just where the bug was.

During my younger days, after high school, most people would enroll in computer studies and Excel was among the units. I hated it somehow and just attended two classes but as a Data analyst having a solid foundation in Excel makes the rest at least manageable.

Topics

Beginner

  • Introduction to Excel Interface

  • Types of Data Types in Excel

  • Use basic formatting options.

  • Use common functions: SUM, AVERAGE, MAX, MIN

  • Cell Referencing

    Intermediate level:

  • Data Preparation Techniques: Sort and filter, Text to Column, Remove duplicates, Data Validation

  • Text Functions: Upper, Lower, Proper, Left, Right, Trim, Concat, Find, Substitute, Textbefore.

  • Date Functions: Basic date Functions, Converting dates with Values and Text to Data

  • Logical Functions: If, IFS, COUNTIF, SUMIF, AND, OR.

  • Lookup and Array Functions: VLOKUP, HLOOKUP, XLOOKUP, INDEX and MATCH, VSTACK, HSTACK, FILTER, TAKE, SEQUENCE, UNIQUE

Advanced Level:

  • Data Cleaning with Power QUery

  • Conditional Formatting

  • Pivot Charts and Tables

  • Utilize What-If Analysis

  • Data Visualization: Charts, Add trend lines and error bars, work with Sparklines, dashboards.

Expert Level

  • Macros and VBAS

  • Advanced Data Analysis: use array formulas

  • Advanced functions like SUMIFS, COUNTIFS, SUMPRODUCT, INDEX MATCH MATCH.

  • Statistical analysis with tools like Data Analysis ToolPak.

  • Data Integration: Import and export data from external sources

  • Data Models and Power Pivot

  • Collaboration and Data Sharing: Collaborate on Excel workbooks, use Excel Online, and share data securely.

Resources

  1. Microsoft Excel Official Website

  2. LinkedIn learning

  3. Coursera

  4. edX

  5. DataCamp or DataQuest

  6. Youtube:

  7. Udemy

  8. FreeCodeCamp

  9. Udacity

Projects

We've also shared some common data sources already. Those can be utilized to build projects.

Conclusion

Learning is never a linear smooth curve. 1 % learning daily will give you a better improvement list.

Documentation is key and network. No man is an island.

You don't have to master all Excel to be able to move to projects. Once you are comfortable with intermediate functions then you can always continue learning since it never stops.

I believe there are still other better resources out there that I did not include here but for someone who is starting from scratch, I bet this will act as a guide.

Vamos Practicar!