Yes. The records fall into natural groups by funding stage, city, sector and announcement month, though the labels need cleaning first. The dataset has no join keys, so each month is a separate table with the same 13 columns. I did not segment by Amount, which is stored as text and which I did not query. **1. Funding stage (best fit)** - Stage is the cleanest classifier. Across the monthly tables, Seed (73), Series A (56), Pre-series A (37), Series B (26), Series C (19), Series D (14) and Series F (12) are the main categories. - A sensible grouping is early (Pre-seed, Seed, Pre-series A), growth (Series A–C) and late (Series D and beyond), with undisclosed or blank as its own group. - About 127 rows have a blank stage and 37 more say "undisclosed", so roughly a third of records can't be placed. - Variants should be merged: "Preseed" and "Pre-seed", "undisclosed", "Undiclosed" and "Unknown", "Series-D" and "Series D", and "$Series A" and "Series A". A few values are not stages at all, such as "Working Capital to SMEs" and an investor-name string. **2. Location (city)** - Bangalore (124) dominates, followed by Mumbai (62), Gurgaon (48), New Delhi (31), Chennai (27), Noida (15), Hyderabad (14) and Pune (12). - "Bengaluru" (10) is the same city as Bangalore, so those should be combined. - Delhi, Gurgaon and Noida could be merged into an NCR region. - 20 rows have no location. **3. Sector** - Financial Services leads (59, plus 13 as "Financial services"). Next come IT & Services (27), Computer Software (26), Health/Wellness/Fitness (15), E-learning (12), E-commerce (12) and Food & Beverages (11). - There are 40–55 distinct sector labels per month, with overlap such as Software and Computer Software. Rolling them up into 8–10 broader themes such as fintech, software and IT, health, education, commerce and food would work better. - 19 rows have no sector. **4. Announcement month** - The five tables (January to May 2022) are themselves a time segmentation. January has the most rows (115) and May the fewest (42). - May has some misaligned or blank rows, so treat it with caution. **Suggested approach:** use stage (cleaned) × city or sector as the main segmentation, with month as a time view. Standardise the spelling variants first and handle the blank and undisclosed stage rows separately.