What is data analytics for businesses?
El data analysis for businesses It involves collecting, cleaning, and interpreting the information generated by a business (sales, customers, costs, campaigns, staff) to turn it into decisions. It's not about accumulating data, but about answering specific questions with it.
And more and more companies need it. According to the latest INE survey on the use of ICT in companiesAccording to a report published in October 2026, 33,6% of Spanish companies with 10 or more employees were already using artificial intelligence in the first quarter of the year. A year earlier, this figure was 21,1%. Without well-organized and well-interpreted data, that AI isn't very useful.
The labor market is heading in the same direction. Future of Jobs Report 2025 The World Economic Forum identifies big data specialists as the fastest-growing profession by 2030, ahead of fintech engineers and AI specialists. Conversely, manual data entry jobs are among those experiencing the greatest decline.
The good news: if you already work for a company, you're halfway there. In this guide, we explain how to become a data analyst based on your professional background and why your experience works in your favor.
Data analyst with no experience: why your profile is an advantage
Many people believe that working with data requires an engineering or math background. That's not the case. You can learn the tools in months; understanding how a business works takes years.
A good analyst isn't the one who knows the most formulas, but the one who asks the right questions: why is a campaign's conversion rate dropping, which customers are most at risk of leaving, or which product is eating up the margin? And those questions are best formulated by someone who knows the area from the inside. That's why data analysis for businesses needs professionals who understand the business, not just the technical aspects.
| If you're coming from… | You already handle data from… | You can evolve into… |
|---|---|---|
| Marketing | Campaigns, web traffic, leads, social media | Marketing Data Analyst |
| Finance and management control | Budgets, costs, profitability | Business Intelligence Analyst |
| Sales and ecommerce | Orders, customers, prices, returns | Ecommerce Data Analyst |
| Human Resources | Staffing, turnover, absenteeism, selection | People Analytics |
| Operations and logistics | Stock, deadlines, suppliers, incidents | Operations Analyst |
In all cases the leap is the same: going from to receive reports to build them and draw conclusions from them.
What you need to learn (and what you don't)
The essential point is:
- Advanced ExcelPivot tables, lookup formulas, and data cleaning. It's the foundation of almost everything.
- A visualization toolPower BI is the most widely used tool in companies for creating dashboards and reports.
- Basic SQL concepts: to extract data from the company's databases without depending on another department.
- Python (optional at the beginning): very useful if you want to automate tasks or move towards a more technical profile.
- Basic statistics: averages, trends, correlations and knowing when a piece of data is reliable.
- Telling stories with dataA graph alone is not enough to convince; you have to explain what it means and what to do.
- AI and data governanceHow to use AI tools for analysis and what legal and ethical limits must be respected.
How to make the leap into data analysis: 5 steps
- Start with a problem in your area. Choose a real question from your work (why are sales of a product declining, which channel brings in the best customers) and try to answer it with data. It's the best way to learn and demonstrate your value.
- Master a visualization tool. With Power BI, you can connect data sources, cross-reference them, and create dashboards that your team uses daily. You'll notice the difference in just a few weeks.
- Build a small portfolio. Two or three well-explained analyses, using anonymized data from your company or public data, are worth more than any line on your resume.
- Prove what you know. An official certification demonstrates to your company, or a new one, that you have mastered the tools and understand the business. We explain which one to choose in the next section.
- Position yourself within your company. Offer to set up your department's tracking dashboard or to analyze project results. Many analysts start this way, in a hybrid role, before moving on to a more permanent position.
Which certification to choose to start with
There are two official certifications that are a great fit if you're coming from a company: the Microsoft PL-300 (Power BI Data Analyst)designed for business, marketing, and finance profiles, and the Python Institute PCEDFor those who prefer a more technical profile or want to automate tasks. Neither requires prior experience as an analyst. If you're undecided between the two, we explain it in detail in [link/section/etc.]. Power BI or Python: what to learn first if you come from the corporate world.
Train and get certified at the same time at IUNIT
El Master's Degree in AI and Data Science for Companies from IUNIT It's designed to help you make the leap from any background: you don't need prior experience in data or programming. It's a 60 ECTS degree program, taught in person in Madrid.
- Official certification included. You prepare for and complete the course and official exam through PUE's IT Skills platform, at no additional cost. You choose your learning path based on your profile: Microsoft PL-300 (Power BI) or Python Institute PCED.
- From data to strategy. The program covers big data and cloud, AI and machine learning fundamentals, cybersecurity, digital marketing, ecommerce, and AI regulation and ethics.
- You learn by doing. In the Data Analytics Lab you work with data and challenges from real companies from the first week, in teams that mix business, marketing and technology profiles.
- Real experience. You finish with a Master's Thesis that you can show in your next interview or promotion.
The master's program lasts 9 months.The next call for applications begins in February 2027.
Do you want to make the leap into the world of data? Request information or reserve your place at admissions@iunit.edu.esYou can also contact us by phone at 910 604 413 or via WhatsApp at 646 642 780. See our financing options at [website address]. Admission and Scholarships.
