Yes. Three groupings fit these records well, and a fourth comes from how the data was delivered. Each needs some label cleanup first. **1. Funding stage (the strongest grouping)** - Stage is the clearest lifecycle split (query results step-0 and step-3). - Seed is the largest named stage with 73 records, followed by Series A (56), Pre-series A (37), Series B (26), Series C (19), Series D (14), Series F (12) and Series E (11). - Later stages (G, H, J) have only 1–3 records each, so they are too thin to analyse alone. - A sensible roll-up is **Early** (Pre-seed, Seed, Pre-series A), **Growth** (Series A–C), **Late** (Series D and beyond) and **Undisclosed**. - The stage column is messy: - 127 records have a blank stage, the largest single group. - 37 are "undisclosed", with variants such as "Undiclosed" and "Unknown". - There are spelling variants: "Preseed" vs "Pre-seed", "$Series A", "Series-D", "Series B1", "Series F2". - At least one cell holds investor names (a misaligned row), plus a stray "Working Capital to SMEs". - Merge these variants before using stage as a segment. **2. Sector (the industry grouping)** - Financial Services leads with 59 records, then Information Technology & Services (27), Computer Software (26), Health, Wellness & Fitness (15), E-learning (12), E-commerce (12) and Food & Beverages (11) (step-1). - Sector has roughly 20 to 55 distinct values per monthly table, so it is a long tail. - It needs consolidation. "Financial Services" and "Financial services" are counted separately, as are "Software" and "Computer Software". - 19 records have a blank sector. - A hand-built mapping into about 8–10 broad verticals would work better than the raw values. **3. Location (the geographic grouping)** - Bangalore dominates with 124 records, then Mumbai (62), Gurgaon (48), New Delhi (31), Chennai (27), Noida (15), Hyderabad (14) and Pune (12) (step-1). - "Bangalore" and "Bengaluru" are the same city, with 124 and 10 records. Merging them makes Bangalore even larger. - 20 records have a blank location. - Gurgaon, New Delhi and Noida could be rolled up into one NCR region. - The long tail of smaller cities could go into an "Other" group. **4. Announcement month (the time grouping)** - The data is delivered as five monthly tables, January to May 2022, with 115, 96, 98, 95 and 42 rows respectively. - Each table is one month's funding rounds, so month is a natural cohort. - May is much smaller, and the dataset notes say some of its rows are misaligned or blank, so compare it cautiously. **Practical recommendation:** Start with **stage tier × sector vertical**, and use **city or region** as a secondary cut. Most of the counts above come from the stage, sector and location columns of the five monthly tables combined. Company founding year and funding amount are less useful as groupings: Amount is stored as text and would need parsing first, and I did not profile it here.