In our previous guide on data analytics courses in Pune (2026), we explained what a strong curriculum should include: Excel, SQL, Python, BI tools, statistics, projects and placement support. That article focused on what you learn.
This article focuses on what you can actually do with those skills. It showcases real‑world Excel dashboard projects created by our Data Analytics students in Pune – projects they were proud enough to publish on LinkedIn as part of their professional portfolios.
How These Student Projects Fit Into Our Data Analytics Course
Before we dive into each project, it helps to understand how they fit into a typical, industry‑aligned data analytics course syllabus:
- Students start with Excel and learn data cleaning, formulas, pivot tables, charts and dashboarding.
- They practice end‑to‑end Excel analytics projects: importing data, cleaning it, analyzing it, and then building interactive dashboards with slicers and KPIs
- They work with popular practice datasets like Global Superstore, a well‑known retail dataset with tens of thousands of orders across countries, segments and product categories.
- Along the way, they learn to translate raw business questions (e.g., “Which region is most profitable?”) into clear charts, metrics and insight‑driven narratives.
This is how our students are thinking like analysts and building dashboards that could be plugged directly into a real business.
Students Projects
1. Sneha Kulkarni – Excel Dashboard as a Launchpad for Career Transition
Sneha comes from an academic background and currently works as an Assistant Professor, while actively upskilling in Data Analytics with tools like Excel, SQL, Power BI, Tableau and Python. Her project post highlights both an Excel dashboard and her career transition journey from teaching to data‑driven roles.
In this Excel analytics/dashboard project Sneha demonstrated :
- A raw transactional dataset and cleaned it using Excel features like Power Query, text functions, and duplicate removal.
- Built a pivot tables and charts to summarize data by time, category, geography, or customer segment.
- Created an interactive dashboard using slicers, timelines, and dynamic charts, so non‑technical stakeholders can explore the data themselves.
Learning outcomes from Sneha’s work
- Can own a complete Excel analytics workflow, from raw data to dashboard.
- Understands how to communicate insights visually, not just crunch numbers.
- Has the confidence to showcase her work publicly, an important step in any career transition into data analytics.
2. Sayyed Abdussami – Excel Data Analytics Dashboard for Business Insights
Sayyed’s project focused explicitly on an Excel data analytics dashboard, which aligns perfectly with what entry‑level data analyst roles expect: being able to take raw Excel data and turn it into insightful, interactive reports.
His data analytics project includes:
- Problem framing: e.g., “How is our sales performance by region, product and time?”
- Data preparation: cleaning columns, handling missing values, standardizing categories and building calculated fields such as revenue, margin or growth rate.
- Dashboard design: arranging key performance indicators (KPIs), trend charts and breakdowns logically on a single page, using color and layout for clarity
Learning outcomes from Sayyed’s work
From a recruiter’s point of view, a project like Sayyed’s proves that he can:
- Translate ambiguous business questions into measurable KPIs and visuals.
- Build clean, usable dashboards that answer “Where are we doing well?” and “Where do we need to improve?” without requiring technical jargon.
- Apply advanced Excel techniques (pivot tables, slicers, formulas) in a way that delivers direct business value.
This is exactly the kind of portfolio piece that supports applications to data analyst roles in Pune and complements the theoretical topics covered in our 2026 course guide.
3. Mashaarat Mujavar – Global Superstore Analysis in Excel
Mashaarat’s project is built on the famous Global Superstore dataset – one of the most widely used practice datasets in the world for retail analytics. This dataset contains around 50,000 orders with details about customers, products, regions, sales, profit and shipping over several years, making it ideal for end‑to‑end analytics.dataanalyticsteam2.hashnode+2
His Project on Global Superstore generally involved:
- Data understanding & cleaning: handling 20+ columns including order dates, ship dates, segment, category, sub‑category, region, sales, discount, profit and shipping cost; fixing data types and missing values.medium+1
- Feature engineering: creating fields like delivery days, profit margin, price per quantity, and time‑based breakdowns (year, month, quarter).medium+1
- Insightful dashboards:
- Sales and profit by region and market
- Top‑performing categories and products
- Impact of discount strategies on profit
- Time‑series trends for sales and returnsdataanalyticsteam2.hashnode+1
Learning outcomes from Mashaarat’s work
By successfully delivering a Global Superstore Excel dashboard, Mashaarat demonstrates that they can:
- Handle larger, more complex datasets similar to what many real companies track.
- Discover deeper retail insights like “Which region brings the most profit?” and “Which categories struggle despite high sales?”
- Use Excel as a lightweight business intelligence (BI) tool, not just a spreadsheet.
This kind of project clearly shows recruiters that our students are ready for sales, operations and retail analytics roles, not just academic exercises.
4. Varsha Kutumbale – Career Transition, Upskilling and Continuous Learning
Varsha is aspiring data professional who has moved from content‑focused roles into analytics, with strong interest in Excel, Power BI and dashboard development. Her project post emphasize career transition, upskilling and continuous learning.
In this Data Analytics course, Varsha has :
- A non‑traditional background (e.g., content, writing, humanities) coming into analytics and proving that data is not only for engineers.
- A structured path of upskilling – from Excel fundamentals to BI tools, and from basic charts to well‑designed dashboards
- A mindset of continuous learning – using each project and LinkedIn post as a stepping stone towards stronger roles and responsibilities.
Learning outcomes from Varsha’s work
Varsha’s project underscores that:
- Data analytics is open to graduates from any stream who are willing to put in consistent practice – That’s what we teach in our data analytics course in Pune
- Soft skills like storytelling, documentation and communication (coming from her content background) are powerful differentiators for data analysts.
Varsha’s project is living proof that the course is not just about tools it’s about transforming careers.
5. Tanvi Kokare – Banking and Finance Analytics in Excel
Tanvi comes from a commerce background with a specialization in Banking & Finance, and is now focusing on how data analytics supports financial decision‑making. Her project combines an Excel dashboard with a banking and finance domain, which is a powerful combination for roles in finance analytics and reporting
Her Banking/finance dashboard in Excel focus on:
- Portfolio or product performance: analyzing loans, deposits, credit cards or investment products by segment and geography.
- Risk and profitability: tracking non‑performing assets (NPAs), default rates, interest income, and profit margins over time.
- Regulatory and management reporting: summarizing key figures in visual formats that senior management can review quickly.
Learning outcomes from Tanvi’s work
Tanvi’s project highlights:
- Strong synergy between domain expertise (Banking & Finance) and technical analytics skills, a combination that is highly valued in financial institutions.
- Ability to translate raw finance data into clear, management‑ready dashboards in Excel.
- Readiness for junior roles in MIS reporting, business analyst – finance, or risk and portfolio analytics.
For prospective students, this shows that your Data Analytics course does not lock them into a single industry they can leverage analytics in the domain they already know best.
Why These Projects Matter for Future Students
If you are considering enrolling in a data analytics course, here is what you should take away:
- You are not just signing up to “learn Excel” you are signing up to build real dashboards that you can show on LinkedIn and in interviews.
- You do not need to be from an engineering background; students from academia, content, commerce and banking are already succeeding through structured upskilling.
- A good course is proven not by its brochure but by its students’ public work and these five projects are exactly that proof.
So summary: If you are looking for a Data Analytics Courses, learn :
- What a good data analytics course includes: Excel, SQL, Python, Power BI/Tableau, statistics, EDA, intro ML and projects.
- Data analytics course duration (typically 4–6 months for job‑oriented programs in Pune) and realistic fee ranges.
- Who is eligible for data analyst roles and how freshers from any stream can start their journey.
Envision Offers the best data analytics course, students who completed our course showcase tangible outcomes :
- Tool Mastery in Real Projects
- Students like Sneha, Sayyed and Mashaarat prove that Excel is not just taught in theory, they can build full dashboards that answer real business questions.
- Domain‑Specific Application
- Through Global Superstore and banking/finance themed dashboards, students are learning to apply analytics in retail and financial domains, two of the biggest employers for data analysts.
- Career Transition and Upskilling Stories
- Varsha and Tanvi show that with the right guidance, career transitions from non‑IT backgrounds into analytics are realistic, especially in a city like Pune where analytics talent is in high demand.
- Portfolio‑Ready LinkedIn Presence
- All five students have taken the professional step of sharing their work publicly on LinkedIn, which is exactly how hiring managers and recruiters discover data analyst portfolios today.