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rademar's avatar
rademar
Frequent Visitor
2 years ago
Solved

API connection, time series analysis issue

Hi Everyone,   I've never userd API as a data source so far (always had a direct access to db). But for this project I got API documentation and I don't have a clue what to do...   This is a smal...
Need Help
  • lbendlin's avatar
    lbendlin
    2 years ago

    Choose a balance between reducing the strain on the source system (pull only the data that you need) and your maintenance effort (DB management) .  Instead of a db you can also consider CSV or Parquet files for your storage.

lbendlin's avatar
lbendlin
Super User
2 years ago

Choose a balance between reducing the strain on the source system (pull only the data that you need) and your maintenance effort (DB management) .  Instead of a db you can also consider CSV or Parquet files for your storage.

rademar's avatar
rademar
Frequent Visitor
2 years ago

Hm.. CSV sounds like interesting idea..

 

If I got this right: Make scheduled API call each day and save it as csv file in some shared folder (google drive for example). Use that folder as data source for the table in PowerBi. Each day when new csv shows up in that folder it's appended to that table in pbi. If there's some change in previous data, I can manually make api call for that day and change that day's csv file.  Sounds right? 

I guess auto refresh shouldn't be an issue since it's possible to do it if data is in shared folder?

  • lbendlin's avatar
    lbendlin
    Super User
    2 years ago

    Correct. CSVs ingest very fast, so you can do a full load of all CSV files in that folder each time if you want to minimize the maintenance effort.