Quick Answer
- Data Science has a higher average salary in Canada, but requires a STEM degree and coding skills.
- SAP has no formal degree requirement and a faster path to a first role for the right background.
- Accounting/finance backgrounds transfer directly into SAP FICO, not Data Science.
- Data Science suits people drawn to statistics and programming specifically.
- Neither is objectively "better" — they suit genuinely different starting points.
SAP consulting and Data Science get compared often because both are seen as strong, in-demand technology-adjacent careers — but they're built on fundamentally different skill foundations.
SAP consulting centers on configuring and supporting enterprise business processes — finance, procurement, sales — inside a structured software system, drawing heavily on business-process knowledge. Data Science centers on extracting insights from data using statistics, programming, and machine learning, drawing heavily on quantitative and technical skill. They can overlap (SAP itself increasingly includes analytics and AI tooling), but as career starting points, they ask for genuinely different strengths.
On raw average numbers, Data Science edges ahead — but that comparison alone is incomplete without accounting for the very different entry requirements covered next.
- No mandatory formal degree requirement
- Existing business background (accounting, logistics, sales) transfers directly
- Structured training typically 9-12 weeks to job-ready
- Most roles expect at least a bachelor's degree in a quantitative field
- Competitive roles often prefer a master's degree or PhD
- Requires building programming and statistics skills, often from scratch
For someone without a programming or statistics background, Data Science is generally the steeper climb — it requires genuine proficiency in Python, SQL, and statistical methods built largely from zero, since most business backgrounds don't transfer this kind of technical skill directly. SAP FICO, MM, or SD, by contrast, can be learned by leveraging existing business-process knowledge (accounting, logistics, sales) without needing to learn to code at all, which is a meaningfully shorter and more forgiving path for someone coming from a non-technical background.
Neither path is objectively "better" — they suit different people. Be honest about which of these sounds like you.
Choose SAP if...
You have or want to build on business-process knowledge (finance, logistics, sales), prefer structured configuration work over open-ended analysis, and want a faster path to a first role without a STEM degree.
Choose Data Science if...
You're genuinely drawn to statistics, programming, and pattern-finding in data, are willing to invest in formal education, and want to work across a broader range of industries and problem types.
Consider the hybrid path if...
You want SAP's accessible entry point now, with room to develop SAP Analytics Cloud or AI-adjacent skills later as a specialization within an established SAP career.
Skip the degree.
Start with what you already know.
Live SAP FICO, MM, SD, and User Level training with real hands-on system access and full career support — no STEM degree required.
*93% placement outcomes among students who completed the programme and engaged with placement support. Individual outcomes vary.