Tauseef FayyazA to Z
Glossary
Every concept in this sheet, plus the smaller terms it uses. Select a concept to open its card.
A
- A good business question
- A specific, answerable question tied to a decision: who is asking, what they will do with the answer, which metric, which period and which comparison.
D
- Data validation
- Rules on cells that limit what can be entered, such as a drop-down of allowed regions or dates within a range.
F
- FILTER, UNIQUE and SORT
- Functions that return a whole range of results that spill into neighbouring cells: a filtered list, the distinct values or a sorted copy.
M
- Metrics and KPIs
- A metric is a precisely defined number, such as weekly active users.
P
- Personal data and privacy
- Information that identifies a person, such as names, phone numbers, emails or national ID numbers, and the rules for collecting, storing and sharing it.
- Pivot tables
- A tool that summarises a table by dragging fields into rows, columns, values and filters, such as total sales by region and month.
R
- Raw, working and output tabs
- Keeping untouched source data on one tab, cleaning and calculations on another, and the summary or chart on a third, with a notes tab describing each.
- Relative and absolute references
- A relative reference (A2) shifts when you copy a formula; an absolute one ($A$2) stays fixed; a mixed one ($A2 or A$2) fixes only the column or row.
S
- Structured tables
- A range turned into a named table, whose formulas refer to columns by name and which grows automatically when you add rows.
- SUMIFS and COUNTIFS
- Functions that sum, count or average only the rows that meet one or more conditions.
T
- Text and date cleaning functions
- Functions that fix the usual mess: extra spaces, mixed case, text that should be numbers or dates, and codes that need splitting.
- The analysis workflow
- The loop most analyses follow: ask the question, prepare and clean the data, analyse it, share the result and help people act, then check whether the action worked.
- Tidy data
- A table where each row is one observation, each column is one variable and each cell holds one value.
- Types of analysis
- Descriptive says what happened, diagnostic asks why, predictive estimates what will happen, and prescriptive suggests what to do.
W
- What a data analyst does
- Answers business questions with data: finds and cleans the data, analyses it, and explains what it means and what to do next, usually through reports, dashboards and short write-ups.
X
- XLOOKUP
- Looks up a value in one column and returns the matching value from another, with a fallback when nothing is found.