**Yes. The dataset has 12 exact duplicate rows, and possibly one near-duplicate.** - **Exact duplicates:** The table has 300 rows but only 288 distinct `User_ID` values, so 12 IDs appear more than once. All 12 repeated IDs appear exactly twice (U0055, U0059, U0085, U0104, U0116, U0138, U0151, U0188, U0244, U0254, U0279, U0280). - **Identical across all columns:** The check on all content columns also found 12 groups. Each repeated `User_ID` therefore has a second copy that matches on every content field, not just the ID. The profile-column check also gave 12 groups. - **Same load:** Each duplicated ID sits in a single ingestion batch and source file. These look like repeats within one load rather than re-ingestion of a later file. - **Possible near-duplicate:** Matching on demographics plus income alone gives 13 groups, one more than the 12 above. One pair of rows shares those fields but has a different `User_ID` or other content. It could be a coincidence or a re-keyed duplicate, and I did not inspect it. Removing the repeats leaves 288 unique users. Any averages or counts over the raw table currently give these 12 users double weight, a 4% inflation of the row count. Deduplicate on `User_ID` before analysing, for example with `SELECT DISTINCT *`.