## Challenge 3: Utilize enriched payment data ### Motivation Until now banks had a very inexact idea of what are their clients spending for. With [TapiX](https://tapix.io) banks can now enrich their transactions with merchant name, GPS location and precise categorization and bring interesting insights to the clients. We’ve prepared a sample dataset for you to play with the data and try to find interesting use-cases. Unfortunatelly GPS coordinates, merchant name, and logos could not be due to the legal reasons provided, but for the challenge, you can assume them to be present. ##### Challenge presentation More information regarding the challenge can be found in the presentation [here](https://www.dropbox.com/s/1xwswhay4bsfje7/TapiX%20-%20HackPrague%20introduction.pdf?dl=0). You can find out more regarding TapiX on its website [tapix.io](https://tapix.io). ##### Prize Money 4 000 CZK for the winning team ### Possible challenge questions * How to help client to save their money? * Can you generate insights for clients using this data? * Can you track positive changes in client’s life based on his transactions? * Can you segment clients based on their transactions? * Can you find any other use of the enriched transactions? ### Provided datasets Dataset of 50k clients card transactions in the past 6 months enriched by [TapiX](https://tapix.io). Each transaction contains client id, her gender approximate year of birth, tx category, shop_type, region as well as merchant_uid and shop_uid- an anonymized name of merchant and shop. The transactions are divided into 22 main categories and 390 tags. A list of categories and tags can be found [here](https://www.dropbox.com/s/bm3okleg8v5mbun/tapix_category_tag_list.xlsx?dl=0). DM Adam Dobiáš on Slack if you would need Category - Tag hierarchy. **Note** GPS coordinates, merchant names and logos could not be provided due to the legal reasons, but for the challenge, you can assume them to be present. E.g. use `merchant_uid` as real merchant name. * Data are available in CSV format in `hackprague-dateio` public S3 bucket * Here is how you connect it to Deepnote 1. Go to **Integrations** on the left and create new Amazon S3 integration 2. Enter a bucket name and integration name `hackprague-dateio` and submit the dialog. 3. Connect the newly created integration `hackprague-dateio`. 4. You can find the connected data in `/datasets/hackprague-dateio`!