In a world driven by numbers, analytics is no longer optional—it’s essential. Whether you’re managing retail performance, healthcare outcomes, HR trends, or financial forecasts, data analytics is the key to better decisions. Yet one question lingers for those considering the field:
Is data analytics hard?
The short answer: It doesn’t have to be. Especially not with tools like Power BI, SSIS, and SSRS that make data analysis faster, smarter, and more intuitive.
This blog will guide you through:
- The truth about the difficulty of data analytics
- How modern tools simplify the learning curve
- How to get started in this thriving field
- Why data analytics is a strong career choice in 2025
- What certifications, skills, and jobs to target
Is Data Analytics Hard to learn ?
Not as hard as you think—just unfamiliar
When people say data analytics is “hard,” they’re often referring to its technical layers—coding, statistics, algorithms. But here’s the truth: the basics of data analytics can be mastered without deep coding or a math degree.
What makes it seem hard:
- Learning too many tools at once
- A lack of guided, real-world practice
- Overemphasis on coding early on
- No clear idea of what analysts actually do
What makes it easier:
- Starting with tools like Power BI or Excel
- Focusing on data storytelling and insights, not just formulas
- Learning through guided, hands-on projects
- Building business context around the numbers
Why Choose Data Analytics as a Career?
Because data powers every industry
From hospitals to retail chains, sports teams to financial firms, and startups to global enterprises, all organizations now rely on data. And that means a rising need for people who can analyze, interpret, and visualize it.
Here’s what makes it a top-tier career:
✅ Booming Job Market
- Entry-level data analyst jobs are available across major sectors—retail, HR, healthcare, finance, tech.
- Platforms like LinkedIn list over 70,000+ data analytics jobs, including remote and part-time roles.
✅ Remote Flexibility
- Many companies, including Amazon and Google, hire remote analysts, giving professionals more freedom and flexibility.
✅ Lucrative Salary Potential
- According to industry benchmarks, salaries for data analysts start at $60K+ and can scale up to six figures with specialization in areas like predictive modeling, people analytics, or financial forecasting.
✅ Strong Career Growth
You can start as an entry-level data analyst and progress to roles like:
- Data Scientist
- Analytics Manager
- Business Intelligence Consultant
- Data Analytics Consultant
How Power BI Makes Data Analytics Easier
A friendly, powerful tool for both beginners and pros
Power BI, Microsoft’s data visualization and business intelligence platform, simplifies analytics so well that even non-technical professionals can build dashboards, track KPIs, and tell data stories.
Here’s how Power BI removes the complexity:
| Feature | Benefit |
| Drag-and-drop visuals | Build charts and dashboards without code |
| Integration with Excel & SQL | Use data you already have |
| Natural language queries | Ask questions like “What were sales last month?” |
| AI-driven insights | Predict trends and anomalies automatically |
| Cloud access | Share reports in real-time across departments |
With Power BI, you can focus more on insights and less on data wrangling. It transforms raw numbers into actionable visuals with just a few clicks.
Tools That Complement Power BI
When paired with other Microsoft analytics tools, Power BI becomes a full-stack solution:
- SSIS (SQL Server Integration Services): Extract, clean, and transform raw data from multiple sources—CRM, ERP, web apps, etc.
- SSRS (SQL Server Reporting Services): Generate structured, paginated reports for business operations and compliance.
- Excel: Use Excel for initial data exploration and upload directly into Power BI for rich visualization.
- SQL: A great addition for analysts who want to query databases directly—simple SQL is enough to start.
How to Get Into Data Analytics — Even with No Experience
Getting started in data analytics doesn’t require a degree in data science or a background in IT. Here’s how to build your path:
1. Learn the Basics
Start with:
- What is data analytics?
- Types: Descriptive, Diagnostic, Predictive, Prescriptive
- Core tools: Excel, Power BI, Google Sheets
2. Choose a Niche or Industry
Are you interested in:
- Healthcare data analytics?
- HR and people analytics?
- Retail performance dashboards?
Pick a domain where your passion or prior experience lies.
3. Get Certified
Certifications add credibility and structure. Top picks include:
- Google Data Analytics Certificate
- Microsoft Power BI Certification
- Healthcare Data Analyst Certification
- WGU – Data Analytics Degree Online
- DataCamp or Coursera bootcamps
4. Build a Portfolio
Your portfolio is your passport. Include:
- 3–4 real-life dashboards using Power BI
- One predictive modeling project (if possible)
- SSIS pipeline setup for a use case (optional)
- SSRS report for structured enterprise data
5. Start Applying
Look for roles like:
- Entry-Level Data Analyst
- Junior BI Developer
- Reporting Analyst
- Data Analytics Intern
Even freelance data analytics work or contract-based roles (like at Refinitiv, Macys, or startups) help you break in.
What Skills Do You Need?
| Skill | Importance |
| Data Visualization | Power BI, Tableau |
| Spreadsheet Mastery | Excel formulas, charts |
| Basic Statistics | Mean, median, variance, correlation |
| Business Acumen | Understanding business questions and KPIs |
| SQL (Optional) | Writing simple queries for data retrieval |
| Communication | Presenting insights in a clear, visual way |
Key Takeaways
- Data analytics isn’t hard—it just needs the right entry point
- Tools like Power BI drastically lower the learning curve
- You don’t need a tech background to start; domain knowledge and curiosity go a long way
- Certifications and hands-on projects are more important than degrees
- Entry-level jobs are growing across industries, especially in retail, healthcare, and HR analytics
Ready to Jumpstart Your Career in Data Analytics?
At BSS Universal, we guide aspiring data professionals and businesses with Power BI consulting, training, and implementation services. Whether you’re exploring a new career or scaling data insights in your company—we can help.
Schedule a Free Discovery Call and unlock your analytics journey today.
Would you like a visual infographic or a downloadable checklist for this blog? I can create that too—just say the word!
FAQs: People Also Ask
Is data analytics hard to learn without experience?
No, it’s not as hard as it seems. With the right tools like Power BI and Excel, beginners can quickly grasp core concepts without needing advanced math or coding. Many free courses and certifications offer step-by-step guidance to help you get started smoothly.
Can I become a data analyst with no coding background?
Yes. Many data analyst roles focus more on business insights, reporting, and visualization than on writing code. Tools like Power BI and SSRS allow you to analyze and present data visually. While coding can be a plus, it’s not essential to begin.
What’s better—data analytics or data science?
Data analytics is a great entry point into the data field, especially if you enjoy interpreting data and making business decisions. Data science is more advanced, involving machine learning and heavy coding. For most professionals, starting with analytics offers a solid foundation.
Is data analytics a good career in 2025?
Yes, it’s one of the fastest-growing and most stable career paths. With more companies relying on data to make decisions, the demand for skilled analysts—especially those with Power BI and business knowledge—is expected to rise steadily in the coming years.
How much can I earn as a data analyst?
Salaries vary, but entry-level data analysts typically earn around $60,000 per year. With a few years of experience, professionals can earn between $80,000 and $100,000, especially in specialized industries like finance, healthcare, or retail analytics.
Do I need a degree to get into data analytics?
Not necessarily. While a degree in data science, business, or IT can help, many successful analysts have entered the field through certifications, bootcamps, or self-learning. What matters most is your ability to work with data, showcase projects, and demonstrate problem-solving skills.
What tools should I learn first for data analytics?
Start with Excel and Power BI—they are widely used and beginner-friendly. As you grow, consider learning SQL for data querying and SSRS or SSIS for reporting and data integration. These tools give you a solid foundation for both entry-level and advanced roles.
How do I build a data analytics portfolio with no job experience?
Focus on real-world datasets available online (like Kaggle or government portals). Create 2–3 Power BI dashboards, a report using SSRS, or a case study using Excel. Document your process, share your insights clearly, and upload your projects to GitHub or LinkedIn to get noticed.