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I have 5-6 tables of which they are quite large. I merged one table at a time and then after merging and select the needed columns I closed and Apply All. I tried a few approaches but they were pulling over 12 million rows over 8 hours.. I believe this is the wrong way. The tables all have a common ID which is EmpID and many columns. When selecting one table to merge another, I did a left join and did NOT check on the 'fuzzy matching'. Should that be checked. How can I just get a small subset of the data like 2-3 years instead of everything (10-15 years of data). Also is Merging the better approach? As the 5 tables a lot of the data are quite similar but some are different. They are employee tables with things like Overtime, days off, balance leave, annual leave taken, etc.
When this dashboard is complete and push to production do I need to change the parameters back to getting all data? Organization have premium capacity.
Are these tables have same number of columns and column headers?
If yes - You can consider append tables (or)
And if you want to filter out the data only for last 2-3 years you can filter the data if you have date or year column in all the tables.
BTW, what is your source?
Thanks,
Arul
They are similar but different column names the same names ones are like ProjectSeq, EmpID, location, but other columns all different. I did a Merge as new Query1. I use EmpID as the key to conect to each table and keep adding new tables.... then finally Close and Apply is what took a long time. I did a Keep Rows, it worked fine. When I click on Expand one of the columns to select the tables, it took a long time
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