4 ms·

Agreed, in my experience Excel is an excellent tool for beginners and advanced users. I don't think it has too much to worry about from "tableau"...

by cowls 13y ago

dangoldin 13y ago
Maybe I'm in the wrong circles but many of the "hardcore" quant folk will belittle it. That's why I decided to write something up. I don't think Excel's the right tool for every job but it's a lot more powerful than many people give it credit for.
- chollida1 13y ago
  Interesting, the two quants beside me and myself, all have excel open right now. I guess our fund isn't "hardcore":)
  - dangoldin 13y ago
    Haha - when I was a quant I used it all the time too. We had Perl jobs that would generate Excel reports that would then be distributed to the various PMs so that they could look into the details. I think the finance industry runs on Excel.
    - ardemue 13y ago
      Any industry runs on Excel I guess. I work in aeronautics and everyone who works on a computer maintains some Excel spreadsheets. It's everywhere but so few people know how to use formula, pivot tables, etc, that it has become a real competitive advantage to master them.
  - dons 13y ago
    If they don't have vim or emacs open, they're not hardcore.
- jasonpbecker 13y ago
  I belittle it. A lot. And rightfully so. It's fine if you want to keep a small budget or a quick bit of work with numbers, but it's awful for dealing even modest amounts of data and here's why: Nothing you do is captured and everything is destructive. Any time someone edits their spreadsheet they are irreparably altering the data without real documentation. Excel encourages moving, shaping, dragging, and futzing that may be easier, but ultimately can cause major problems because there's no audit trail. Ever try and replicate something modestly sophisticated that was done in Excel? Good freaking luck. There's nothing wrong with Excel for some basic graphs and calculations. The problem is when people start to use Excel as a data base or as a serious tool for analytics (like some of those business folks).
  - smacktoward 13y ago
    What's needed is a "serious tool" that's as easy for people to get into and understand as Excel is. Excel is as ubiquitous as it is because the mental model of a spreadsheet is very simple and easy to wrap one's brain around. Here's a grid of cells, type stuff into them. Boom, you're an Excel user. (It can do a lot more than that, of course, but many many many people never realize that and still get lots of value out of it. Which is kind of remarkable, really.) Proper databases are much more powerful, but none of them present the user with an interface whose basic metaphors are as immediately obvious as Excel's. You have to learn about tables, data types, relations, etc. to get anything done in them. Most of that stuff comes up with Excel too, but you don't need to know it to get started. The Excel user's first baby steps are much smaller than the database user's are. Given a choice between a flawed tool that's immediately understandable and a perfect tool that requires learning, people will always choose the flawed-but-understandable tool. So they go with Excel.
    - pyoung 13y ago
      I don't think we should necessarily aim to make "serious tools" easy for people to get into. I am not saying that the UI shouldn't be intuitive, but rather that making something 'too easy' results in low barriers to entry and you end up with the wrong types of people using that tool. Excel is very useful (I use it much in the same way the OP does), but it has it's limitations. Because it is so easy to get into, it's easy for individuals lacking the proper experience to over extend themselves. I think much of the explosion in data science jobs these last few years isn't really about "big data", but rather the fact that your typical corporate analyst does not have the experience to tackle mid range data analysis jobs because the only tool they have under their belts is Excel. What really is needed is a larger number of people with experience in statistics, scientific computing (Python, R etc..), and database systems. The current tools we have are fine, they just need to be used properly (well, we should always strive to improve our tools, but you get the idea).

Agreed, in my experience Excel is an excellent tool for beginners and advanced users. I don't think it has too much to worry about from "tableau"...

by cowls 13y ago

Agreed, in my experience Excel is an excellent tool for beginners and advanced users. I don't think it has too much to worry about from "tableau"...

dangoldin 13y ago

Maybe I'm in the wrong circles but many of the "hardcore" quant folk will belittle it. That's why I decided to write something up. I don't think Excel's the right tool for every job but it's a lot more powerful than many people give it credit for.

chollida1 13y ago
Interesting, the two quants beside me and myself, all have excel open right now. I guess our fund isn't "hardcore":)
- dangoldin 13y ago
  Haha - when I was a quant I used it all the time too. We had Perl jobs that would generate Excel reports that would then be distributed to the various PMs so that they could look into the details. I think the finance industry runs on Excel.
  - ardemue 13y ago
    Any industry runs on Excel I guess. I work in aeronautics and everyone who works on a computer maintains some Excel spreadsheets. It's everywhere but so few people know how to use formula, pivot tables, etc, that it has become a real competitive advantage to master them.
- dons 13y ago
  If they don't have vim or emacs open, they're not hardcore.
jasonpbecker 13y ago
I belittle it. A lot. And rightfully so. It's fine if you want to keep a small budget or a quick bit of work with numbers, but it's awful for dealing even modest amounts of data and here's why: Nothing you do is captured and everything is destructive. Any time someone edits their spreadsheet they are irreparably altering the data without real documentation. Excel encourages moving, shaping, dragging, and futzing that may be easier, but ultimately can cause major problems because there's no audit trail. Ever try and replicate something modestly sophisticated that was done in Excel? Good freaking luck. There's nothing wrong with Excel for some basic graphs and calculations. The problem is when people start to use Excel as a data base or as a serious tool for analytics (like some of those business folks).
- smacktoward 13y ago
  What's needed is a "serious tool" that's as easy for people to get into and understand as Excel is. Excel is as ubiquitous as it is because the mental model of a spreadsheet is very simple and easy to wrap one's brain around. Here's a grid of cells, type stuff into them. Boom, you're an Excel user. (It can do a lot more than that, of course, but many many many people never realize that and still get lots of value out of it. Which is kind of remarkable, really.) Proper databases are much more powerful, but none of them present the user with an interface whose basic metaphors are as immediately obvious as Excel's. You have to learn about tables, data types, relations, etc. to get anything done in them. Most of that stuff comes up with Excel too, but you don't need to know it to get started. The Excel user's first baby steps are much smaller than the database user's are. Given a choice between a flawed tool that's immediately understandable and a perfect tool that requires learning, people will always choose the flawed-but-understandable tool. So they go with Excel.
  - pyoung 13y ago
    I don't think we should necessarily aim to make "serious tools" easy for people to get into. I am not saying that the UI shouldn't be intuitive, but rather that making something 'too easy' results in low barriers to entry and you end up with the wrong types of people using that tool. Excel is very useful (I use it much in the same way the OP does), but it has it's limitations. Because it is so easy to get into, it's easy for individuals lacking the proper experience to over extend themselves. I think much of the explosion in data science jobs these last few years isn't really about "big data", but rather the fact that your typical corporate analyst does not have the experience to tackle mid range data analysis jobs because the only tool they have under their belts is Excel. What really is needed is a larger number of people with experience in statistics, scientific computing (Python, R etc..), and database systems. The current tools we have are fine, they just need to be used properly (well, we should always strive to improve our tools, but you get the idea).