Excel and Google Sheets solve many administrative, operational, and analytical tasks. The problem is usually not “knowing too few formulas,” but building workbooks that are difficult to maintain: ambiguous headers, data mixed with subtotals, manually copied formulas, and reports nobody can reproduce.
This guide absorbs the former separate Google Sheets page. For most fundamentals—tables, validation, formulas, filters, and analysis—it is more useful to learn both as variants of the same discipline: working with tabular data clearly and verifiably.
Start with a clean structure
A working table should, where possible, have:
- one row per record;
- one column per variable;
- unique, understandable headers;
- dates stored as dates rather than mixed text;
- numbers without units embedded in the cell value;
- categories written consistently;
- no subtotal rows inside the source dataset.
Keep source data separate from reports. If users enter information manually, identify which columns are editable and which contain formulas.
Learn functions by problem
Do not memorize a list of one hundred functions. Learn families of problems.
Conditions
IF, IFERROR, and conditional functions express rules. Use them carefully: a formula with too many nested levels can be harder to audit than a clearly named helper column.
Aggregation
SUMIF, SUMIFS, COUNTIF, and related functions summarize by criteria. Before writing the formula, define what each criterion represents.
Lookup and relationships
XLOOKUP, VLOOKUP, INDEX, and MATCH solve different ways of relating tables. Do not assume that the same function or syntax is available in every version of Excel or Sheets.
Text and dates
Splitting names, normalizing codes, extracting text, and calculating intervals can be useful, but first check whether formulas are being used to compensate for a source-data problem that should be corrected upstream.
Data validation
A good workbook tries to prevent predictable errors:
- controlled lists for categories;
- restrictions for dates or numbers;
- clearly identified required fields;
- notes or messages when a column has a special rule.
Conditional formatting can highlight exceptions, but it should not replace actual validation when invalid data must be blocked.
Pivot tables and summaries
A pivot table can summarize data without a large collection of manual formulas. Practice with concrete questions:
- sales by month and category;
- cases by owner and status;
- expenses by cost center;
- inventory by location.
Always check the source range, active filters, and refresh date. A report can look correct while missing new rows.
Charts: less is usually better
A chart should answer a question. Before creating it, write the sentence you want to evaluate, such as “how did the monthly total change?” or “which categories concentrate the most cases?”.
Avoid decorative effects that make magnitudes harder to compare. Keep units, period, and source visible.
Excel or Google Sheets: how to choose
There is no universal winner.
Excel may be preferable when you need specific desktop capabilities, complex existing workbooks, Power Query, advanced models, or other Microsoft ecosystem features.
Google Sheets can be convenient for browser-based collaboration, forms, and workflows integrated with Google Workspace.
Both products evolve. Verify the specific capability you need in the version and plan your organization actually uses before designing a process around it.
Collaborate without destroying the workbook
When several people edit:
- define the file owner;
- restrict editable ranges when appropriate;
- use comments for decisions instead of unexplained colors;
- preserve relevant history or versions;
- avoid emailing copies named
report-final-v7-now-really-final.xlsx; - document where the data comes from and how often it is updated.
A useful exercise
Take a sales, inventory, or incident list and build:
- a
Datasheet without subtotals; - validation for categories and status;
- one clearly named calculated column;
- a pivot table with a monthly summary;
- a chart that answers a question;
- a
READMEorNotessheet with source, refresh date, and editable fields.
Then ask another person to update the workbook without your help. If they do not know what to touch, the file still depends too heavily on implicit knowledge.
When to stop using a spreadsheet
A spreadsheet may no longer be the right tool when you need, for example:
- many concurrent writes with complex rules;
- detailed record-level permissions;
- strict centralized auditability;
- data relationships that are difficult to maintain;
- transactional processes that cannot tolerate duplicates or accidental edits;
- automation that has effectively become a full application.
At that point a database, application, or specialized tool may be more appropriate. Do not turn a spreadsheet into an enterprise system merely because it already exists.
Does Crezendo offer Excel or Sheets training?
Availability must be confirmed. Use Contact, describe the group's level, the files they use, and the outcome they need. You do not have to ask for abstract “advanced Excel”; a real case helps define useful training.
Frequently asked questions
Should I learn Excel before Google Sheets?
Not necessarily. Tabular-data fundamentals transfer between them. Learn with the available tool, then identify differences in functions and collaboration.
Are the formulas the same?
Many are similar, but names, arguments, and availability can differ. Check the documentation for the tool and version you use.
Do I need macros to be advanced?
No. A well-structured workbook with validation, reproducible analysis, and documentation can be more valuable than a macro that is difficult to maintain.
When should I use Power BI?
When you need modeling, transformation, visualization, or report distribution beyond what is reasonable in a spreadsheet, it can be an option. Review the Power BI learning path and evaluate your actual case.
