Yes, there are three natural ways to segment these records, plus one structural split. All of them need some cleaning first. The counts below come from the stage, location and sector breakdowns I ran across the five monthly tables. **1. Funding stage (the strongest grouping)** - Stage is the most meaningful classifier. It separates early-stage from late-stage rounds, which usually differ in deal size and investor type. - The largest groups are Seed (73), Series A (56), Pre-series A (37), Series B (26), Series C (19) and Series D (14), followed by Series E, F, G and H. - Before using stage, collapse the variants and gaps: - 127 records have a blank stage and 37 more are "undisclosed". Together these are the biggest segment, so treat them as an explicit "Unknown" group. - Spelling variants should be merged: "Preseed" with "Pre-seed", "Series-D" with "Series D", "$Series A" with "Series A", and "Undiclosed" with "undisclosed". - At least one stage value is actually an investor list ("Blue Ashva Capital, Supack Industries"), and another is a business description ("Working Capital to SMEs"). These are data-entry errors. - A practical grouping is Pre-seed/Seed, Series A/Pre-A, Series B–C (growth), Series D and later (late-stage), and Unknown. **2. Geography (Location)** - Funding is concentrated in a few cities: Bangalore (124), Mumbai (62), Gurgaon (48), New Delhi (31) and Chennai (27). Noida, Hyderabad and Pune follow with 12 to 15 each. - Merge "Bangalore" with "Bengaluru" (10 more). That makes it by far the largest hub. Also merge Gurgaon, New Delhi and Noida into a Delhi-NCR group. - 20 records have a blank location. **3. Industry (Sector)** - Financial Services is the biggest sector (59, plus 13 under the variant "Financial services"). Information Technology & Services (27) and Computer Software (26) follow, then Health, Wellness & Fitness (15), E-learning (12), E-commerce (12) and Food & Beverages (11). - There are roughly 40 to 55 distinct sectors per month, with overlapping labels such as "Software" and "Computer Software". They would need rolling up into 8 to 10 broader themes (fintech/financial services, software/IT, health, education, commerce and so on). - 19 records have a blank sector. **4. Time (the structural split)** - The data is already split by announcement month, January to May 2022. January is the largest table (115 rows), then March (98), February (96), April (95) and May (42). - This is the natural cohort or trend dimension. The May table is thin and has some misaligned or blank rows, so treat it with caution. - Company founding year is a secondary option for grouping by company age (e.g. startups founded in the last 5 years versus older firms). **Recommendation:** The most useful segmentation is Stage × Location hub × consolidated Sector, with month as the time axis. Standardise the labels and keep an "Unknown" bucket first, because blank or undisclosed values make up a large share of the stage field.