IHETC Academy
Becoming a data analyst
They spend most of their time cleaning and checking, not modelling. The skill that sets a good analyst apart is not technical: it is the ability to tell someone expecting a conclusion that the data does not support one.
The job, unvarnished
They spend most of their time cleaning and checking, not modelling. The skill that sets a good analyst apart is not technical: it is the ability to tell someone expecting a conclusion that the data does not support one.
- steps
- 4
- of actual work
- 115 h
- fields covered
- 3
Not connection time.
What the market says
Demand is real but the door is narrow: organisations first hire domain people who can analyse, rather than analysts looking for a domain. That is why this path starts with data and not with tools.
The sequence
Each step assumes the previous one. Taking them out of order is possible, and it is the most common way to lose time.
- 01
Clean data
Collection, cleaning, consistency checks. Eighty per cent of the real work, and the step everyone skips. — about 30 hours of work.
- 02
Analysis and honest reporting
Useful statistics, visualisation that does not lie, stating uncertainty. — about 35 hours of work.
- 03
The business behind the numbers
Understanding the activity being analysed — finance, sales, operations. A context-free analysis serves nobody. — about 25 hours of work.
- 04
Automating without breaking
Making a process reproducible and monitored, knowing where automation becomes risky. — about 25 hours of work.
By the end, you will be able to
- Take a doubtful dataset and establish its reliability
- Produce an analysis that answers the question asked, and say when it cannot
- Build a report readable by a non-technical decision-maker
- Automate a recurring process and monitor its drift
What this path does not give you
This path does not make you a machine-learning researcher: the base holds four advanced-level modules in this field. It makes you operational on analysis and automation, which matches the vast majority of roles actually open in the region.
Questions about this path
Do I need to code before starting?
No. The first two steps can be tackled with spreadsheets and no-code tools, which already creates value. Programming becomes useful at the fourth step, and the path introduces it there rather than as a discouraging prerequisite.
Do I need a computer, or is a phone enough?
A computer is needed from the second step onwards. You can read the lessons and follow your progress on a phone, but you do not clean a dataset or build a dashboard on a six-inch screen. We say so before enrolment rather than at the point where the exercise becomes impractical.