Hands-on Skills
Almost every first job comes with a spreadsheet. Few students have used one for real.
Many students have typed marks into a grid and made a chart for a lab record. Then the first job hands them three thousand rows of untidy data and asks for a summary by Friday. This session puts a working practitioner beside them for that task: clean it, total it, summarise it, and check that the answer is right.
Explore this page7 sections
Listing “MS Excel” on a resume is easy. Using it under a deadline is not.
Spreadsheets sit underneath a great deal of ordinary work: sales reports, attendance, stock, budgets, survey results, lists of leads. A fresher in operations, accounts, HR, sales support or analysis is often expected to work with one from the first week, usually without anybody teaching it.
What is missing is rarely knowledge of a menu. It is the routine: looking at the data before touching it, cleaning it without destroying the original, choosing the simple formula over the clever one, and checking the total before sending it. That routine is learnt fastest by watching someone who does it every day and then doing it yourself.
What the session covers
30 topics across 6 areas. Six parts, in the order the work usually happens.
Looking Before TouchingUnderstand the data first.5
- What one row represents
- What each column means
- Where the data came from
- Blank cells, duplicates and odd values
- Keeping an untouched copy of the original
Most spreadsheet mistakes start with somebody editing data they had not yet read.
Cleaning Messy DataReal data is never tidy.6
The dataset in the room is deliberately untidy, the way a real export from a billing system or a form usually is.
- Trimming extra spaces
- Splitting and joining text columns
- Fixing dates stored as text
- Removing duplicates, carefully
- Consistent spellings and categories
- Filters and sorting without scrambling rows
The Formulas That Do Most of the WorkA short list, used well.5
- SUM, AVERAGE, COUNT and their conditional forms
- IF for simple decisions
- Lookups to bring data together from two sheets
- Absolute and relative references
- Reading an error message instead of deleting the formula
A formula your manager can follow is worth more than one only you understand.
Summarising With a Pivot TableThe question first, then the table.4
- Turning a question into rows, columns and values
- Totals by month, region or category
- Filtering a summary
- When a pivot table is the wrong tool
Making It ReadableSomebody else has to use it.5
- Clear headings and frozen header rows
- Number and date formats
- Conditional formatting, used sparingly
- One simple chart that answers one question
- A short note on what the sheet contains
Checking Your Own WorkThe habit employers notice.5
- Does the total match the source?
- Did the row count change, and why?
- Spot-checking a few rows by hand
- Does the answer make sense?
- Saying what you assumed
Sending a wrong number confidently does more harm than asking a question first.
What participants leave with
- The cleaned file and the summary they built
- A one-page guide to the formulas used
- A checklist for checking a spreadsheet before sending it
- Suggestions for practice data to keep going with
- Pointers to free courses on government platforms such as SWAYAM and Skill India Digital Hub
What this session is not
- A certification course
- Advanced macros or programming
- A tour of every menu
- A promise that one session makes someone an analyst
Who teaches it
- Analysts and operations staff
- Accounts and finance practitioners
- HR and sales operations staff
- Small-business owners who run their business on spreadsheets
How the session runs
Two to three hours, in a small group, with a laptop for each participant or pair. The practitioner opens a realistic, untidy dataset and works through it aloud, including the checks most people skip. Participants then do the same with a second dataset and a question to answer, and the practitioner reviews what they produced. Excel or Google Sheets both work; the routine is the same.
What your students leave with
- A messy, realistic dataset cleaned by their own hands
- The handful of formulas that cover most everyday work
- A summary built with a pivot table, and the habit of checking it
- A clear idea of the level an employer expects from a fresher
- A small finished file they can describe in an interview
- Pointers to free courses for going further
Scheduled sessions
Nothing scheduled yet
Sessions are arranged with a college once a date is agreed. Ask us and we will find the right person for it.
A student rather than a college? See what is coming up, or ask your placement team to host this.
Clean it, total it, check it, then send it.
Tell us who your students are and what stage they are at. Sessions are free for participants.