Google Sheets

Google Sheets Data Entry Practice

Five hands-on Google Sheets exercises you can build yourself to practice real data entry tasks: validation, cleanup, filtering, and lookups.

Updated August 25, 20264 min read

Reading about spreadsheet features doesn't build the muscle memory that real data entry work requires — building small exercises yourself does. Each exercise below takes ten to twenty minutes, uses a blank Google Sheet you set up from scratch, and mirrors a task type that shows up in real jobs. Work through them in order; each one adds a skill the next one assumes you already have.

Before you start

Open a new blank spreadsheet at sheets.google.com. You won't need any template — part of the practice is building the structure yourself, which is closer to what a real task looks like than filling in a pre-made file.

Exercise 1: Manual entry with a header row

  1. 1

    Create headers

    In row 1, type: Name, Email, Phone, City, Signup Date.

  2. 2

    Freeze the header row

    View → Freeze → 1 row, so the labels stay visible as you scroll.

  3. 3

    Enter 25 rows of realistic sample data

    Make up plausible names, emails, and phone numbers. Use a consistent date format throughout, e.g. YYYY-MM-DD.

  4. 4

    Check your work

    Scroll the full range and confirm every row has all five fields filled and the date format never changes.

Expected outcome: a clean 25-row table with a frozen header and zero blank required cells. This is the baseline every later exercise builds on.

Exercise 2: Add data validation

  1. 1Add a sixth column called Status.
  2. 2Select the Status column cells for your 25 rows, then go to Data → Data validation.
  3. 3Set criteria to 'List of items' and enter: New, Contacted, Converted, Inactive.
  4. 4Apply it, then fill in a status for each row using only the dropdown — don't type free text.
  5. 5Try typing an invalid value directly into one cell and observe the warning that appears.

Expected outcome: every Status cell is filled via dropdown, and you've seen firsthand what an invalid entry warning looks like — useful for recognizing it in a real employer's file later.

Exercise 3: Clean up deliberately messy data

Duplicate your sheet as a new tab. In the copy, deliberately introduce messiness: change some emails to ALL CAPS, add extra spaces before some names, duplicate three rows entirely, and leave two Phone cells blank.

  1. 1

    Fix capitalization

    Use =LOWER(A2) in a helper column to normalize emails, then paste the results back as values with Ctrl/Cmd+Shift+V.

  2. 2

    Trim extra spaces

    Use =TRIM(A2) the same way on the Name column.

  3. 3

    Remove duplicates

    Select your range and use Data → Data cleanup → Remove duplicates.

  4. 4

    Fill or flag blanks

    For the two blank Phone cells, either research a plausible replacement approach or mark them clearly, e.g. 'MISSING', so they aren't mistaken for complete records.

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Exercise 4: Filter views and sorting

  1. 1On your cleaned tab, go to Data → Filter views → Create new filter view.
  2. 2Filter the Status column to show only 'New' and 'Contacted' rows.
  3. 3Sort the filtered results by Signup Date, oldest first.
  4. 4Close the filter view and confirm the underlying data and order are unchanged for anyone else who might open the sheet.

Expected outcome: you can produce a narrowed, sorted view of the data without permanently altering the shared sheet — the core benefit of filter views in collaborative work.

Exercise 5: A simple QUERY summary

In a new tab, use QUERY to build a one-line summary of your practice data without touching the original rows.

  • Try: =QUERY(Sheet1!A2:F26, "select F, count(F) group by F", 0) to count rows per status.
  • Then try: =QUERY(Sheet1!A2:F26, "select D, count(D) group by D order by count(D) desc", 0) to see which city appears most.
  • Adjust the range references to match your actual tab and column layout.

Expected outcome: a small summary table that updates automatically if you change the source data — a preview of how QUERY is used for reporting on top of raw entry work.

Repeat with larger data

Once these feel easy, repeat the exercises with 200+ rows of sample data (you can generate placeholder names and emails online) to practice at a volume closer to real assignments.

Turning practice into a portfolio piece

Keep the finished sheet from Exercise 3 or 5 as a small, presentable sample of your cleanup and reporting skills. A short note describing what messiness you introduced and how you fixed it turns a practice exercise into something you can reference when discussing your experience, even without paid work history.

Frequently asked questions

Do I need a template to practice Google Sheets data entry?
No. Building the structure yourself — headers, validation, formulas — is part of the practice and mirrors how real tasks often start from a blank or lightly structured file.
How much practice data do I need for these exercises?
Twenty to thirty rows is enough to learn each feature. Once comfortable, repeat with a few hundred rows to build speed and confidence at a more realistic volume.
Can I use these exercises to build a portfolio?
Yes. Keep a cleaned, well-organized sample sheet along with a short note on what you did, and reference it when discussing your skills even if you don't have paid experience yet.
Is QUERY necessary for entry-level data entry roles?
Not usually required, but being able to build a simple one is a strong differentiator and useful once you move toward reporting-adjacent tasks.

Sources & references

About this article

Published August 25, 2026 · Last reviewed August 25, 2026. Read our Editorial Policy and Disclosure.

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