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Excel users tend to do a far better job of data storage, analysis, and forecasting than most of overpaid SaaS-reliant "modern data team" (Data Engineers, Data A

Excel users tend to do a far better job of data storage, analysis, and forecasting than most of overpaid SaaS-reliant "modern data team" (Data Engineers, Data Analysts, Analytics Engineers, Data Scientists).

bliteben 5y ago
It definitely is a scary business proposition for them to improve Excel and awaken the 800lb gorilla. Microsoft is certainly capable of improving Excel in ways that might even improve the productivity of the entire world. Seems like some of these startups are likely just giving training to future Microsoft employees.
- pete_nic 5y ago
  Agree with this. When battling Microsoft product can matter less than things like contracts and licensing. I have to believe that businesses are spending so much on Azure that they get Office for free (as an analogy - at a previous employer GSuite was nearly free because our AdSense bill was so high). Businesses are unlikely to pay extra for a few more features when they already have Excel and have no plans to move off Azure.
- OzCrimson 5y ago
  Excel is constantly being improved. Are you aware of Power Query? And how about the 14 news functions that were released to Insiders a few weeks ago? Excel Online is far behind the desktop version of Excel but it's making fast progress.
croes 5y ago
I doubt that. Data hoarding, yes. Creating unsupportable spreadsheet solutions, yes.
b-luu 5y ago
Meh, depends on the data teams (and their chosen suite of tools)... Or on the Excel users Both sides can either hack together horrible work-arounds (a matter of "when you have a hammer, everything looks like a nail...") as well as brilliantly thought through solutions. Each tool should be used for it's best use cases, but not bent into what it wasn't designed for! IMHO spreadsheets excel at intuitively manipulating the data ON the data itself. While "modern data" tools (especially dbt) try to convert date teams to use developer best practices... At the expense of less intuitive/direct manipulation of the data. That being said, I think there are also things we could explore in that space: how to make the modern data stack more intuitive?
- datalopers 5y ago
  > how to make the modern data stack more intuitive? I'd start with getting people to learn relational data modeling and SQL [1][2] at a deep level. Stop reaching for python and pandas/spark for every basic data manipulation task or query. Stop adding in layers of Airflow/Dagster/Prefect when a simple cron would work. Stop adding in Kubernetes/GKE/Fargate to manage the aforementioned. Stop moving data between systems constantly (meltano, airbyte, fivetran) when you already have it in a perfectly good place. Stop with the toxic positivity that's completely overflowing the modern-data world and all these bullshit VC-infused startups who are convinced they need every single element and more. 99% of business needs can be satisfied by a single Postgres/Mysql installation and a halfway-competent person armed with SQL and an understanding of normalization. Reach for Excel when you need to do more "hands-on" analysis, business modeling, charting, basic forecasting, and presentation for non-technical users. [1] https://mode.com/sql-tutorial/ https://mode.com/sql-tutorial/ [2] https://use-the-index-luke.com/ https://use-the-index-luke.com/
  - b-luu 5y ago
    Good points, but a bit extremist. I definitely agree with the over-hype making simple mundane tasks way harder than they should be. So yeah, do NOT over-engineer!! But, on the other hand, doing everything with a single Postgres and spreadsheets seems to go with the hammer-to-nail adage. And all too often, you end up with unmaintainable duck-taped hack-arounds... Which is clearly NOT better (nor necessarily worst) than the over-engineered solution. In some cases (maybe not 1% but clearly not the majority either), it does make sense to look at other tools that might be available. That being said, there are waaaay too many options to filter through, because of that darn hype bubble.

bliteben 5y ago

It definitely is a scary business proposition for them to improve Excel and awaken the 800lb gorilla. Microsoft is certainly capable of improving Excel in ways that might even improve the productivity of the entire world. Seems like some of these startups are likely just giving training to future Microsoft employees.

pete_nic 5y ago
Agree with this. When battling Microsoft product can matter less than things like contracts and licensing. I have to believe that businesses are spending so much on Azure that they get Office for free (as an analogy - at a previous employer GSuite was nearly free because our AdSense bill was so high). Businesses are unlikely to pay extra for a few more features when they already have Excel and have no plans to move off Azure.
OzCrimson 5y ago
Excel is constantly being improved. Are you aware of Power Query? And how about the 14 news functions that were released to Insiders a few weeks ago? Excel Online is far behind the desktop version of Excel but it's making fast progress.

croes 5y ago

I doubt that. Data hoarding, yes. Creating unsupportable spreadsheet solutions, yes.

b-luu 5y ago

Meh, depends on the data teams (and their chosen suite of tools)... Or on the Excel users Both sides can either hack together horrible work-arounds (a matter of "when you have a hammer, everything looks like a nail...") as well as brilliantly thought through solutions. Each tool should be used for it's best use cases, but not bent into what it wasn't designed for! IMHO spreadsheets excel at intuitively manipulating the data ON the data itself. While "modern data" tools (especially dbt) try to convert date teams to use developer best practices... At the expense of less intuitive/direct manipulation of the data. That being said, I think there are also things we could explore in that space: how to make the modern data stack more intuitive?

datalopers 5y ago
> how to make the modern data stack more intuitive? I'd start with getting people to learn relational data modeling and SQL [1][2] at a deep level. Stop reaching for python and pandas/spark for every basic data manipulation task or query. Stop adding in layers of Airflow/Dagster/Prefect when a simple cron would work. Stop adding in Kubernetes/GKE/Fargate to manage the aforementioned. Stop moving data between systems constantly (meltano, airbyte, fivetran) when you already have it in a perfectly good place. Stop with the toxic positivity that's completely overflowing the modern-data world and all these bullshit VC-infused startups who are convinced they need every single element and more. 99% of business needs can be satisfied by a single Postgres/Mysql installation and a halfway-competent person armed with SQL and an understanding of normalization. Reach for Excel when you need to do more "hands-on" analysis, business modeling, charting, basic forecasting, and presentation for non-technical users. [1] https://mode.com/sql-tutorial/ https://mode.com/sql-tutorial/ [2] https://use-the-index-luke.com/ https://use-the-index-luke.com/
- b-luu 5y ago
  Good points, but a bit extremist. I definitely agree with the over-hype making simple mundane tasks way harder than they should be. So yeah, do NOT over-engineer!! But, on the other hand, doing everything with a single Postgres and spreadsheets seems to go with the hammer-to-nail adage. And all too often, you end up with unmaintainable duck-taped hack-arounds... Which is clearly NOT better (nor necessarily worst) than the over-engineered solution. In some cases (maybe not 1% but clearly not the majority either), it does make sense to look at other tools that might be available. That being said, there are waaaay too many options to filter through, because of that darn hype bubble.