Using AutoML to predict completion dates of a project management dataset
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02-17-2024 07:05 AM
Hello! I am fairly new to Databricks. I'm trying to do a proof of concept with AutoML in Databricks at my organization, and the dataset I am using is a project management dataset. Here's a sample:
| project_id | market | general_contractor | project_type | permit_date | permit_status | construction_date | construction_status | completion_date | completion_status |
| project_1 | NY | acme inc | rehab | 2/1/2024 | complete | 3/1/2024 | projected | 4/1/2024 | projected |
| project_2 | LA | xyz inc | build to suit | 1/1/2020 | complete | 2/2/2023 | complete | 3/4/2023 | complete |
So based on this dataset, I want to be able to see how I can reduce completion_date period. For example, if I use acme inc in LA, will that reduce my completion date and if so, by how much? or for example if I reduce my permit_date by 2 days, how big of an impact will it have on completion_date? Of course I only have to rely on historical data so all the status fields must be set to "complete".
How do I go about doing this? Also, is there a way to output the result in a way for stakeholder to analyze, using a visual tool like tableau or powerbi?
Thanks!
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