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You and your company are “data -driven”, okay? Certainly, this means the use of highly sophisticated technology to handle data. Having a database in place and asking for it with the SQL seems like the least need in this world.
But what will happen when there are cases when a simple spreadsheet cautioned the written question at a mile distance? Here are many real life conditions.
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1. Your data is small and/or once
Examples of such figures include:
- A CSV from a vendor
- A financial model that has a few hundred rows
- A simple budget prediction
- A Task Tracker
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It would be almost strange to load such data into the database and run some questions. This is exceeded. Open it in Excel or Google Sheets, and you can quickly perform filters, setting and calculations and changes. You may still be setting up tables, indexes and schemes in the database.
2. You need speed and zero setup
If you do not have a relative database, it is necessary to configure:
- A running database, local or cloud
- Default tables and data type
- Appropriate permissions
With a spreadsheet? None of it. Even if installation is needed, it is very fast. But you probably don’t need to install anything, as your machine possibly comes with a pre -installed spreadsheet program, or you can easily use the cloud version.
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You can easily click on the file and move – especially if you just need to see what is in it or run some quick calculation.
3. You need to cooperate
The databases can handle mutual cooperation, but they require permits, describe the character, and SQL knowledge.
For example, supporting Google Sheets is very easy:
- Share a link with your peers
- Add comments
- Track the changes in the file
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If your fellow data team (such as, finance, marketing, operations), it is likely that they do not use SQL – with a spreadsheet, it doesn’t matter.
4. You want to imagine and present the data
SQL is for inquiry and data analysis, but it is not great to present your results. Generally, you export your questions somewhere else. The irony is that it is often a spreadsheet that we were trying to avoid.
If the data is important to be imagined and presented and you can analyze a relatively easily in a spreadsheet, select it more than the SQL. The spreadsheet is both calculations and presentation tools.
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Usually, you will choose more spreadset than SQL if you need:
- Charts for a presentation
- Axis tables for executives
- A financial forecast model
5. Your work is turning and dirty
Examples of such works are to model, to examine minded scenes, and assumptions. This is the place where I will use the spreadsheet.
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You can use them:
- Mental storms financial scenario -> Copy the sheet, compose some cells, and see the results immediately
- Testing assumptions -> Write two formulas, compare them, delete the weak. No scheme is required to migrate
- Instant -model -> Create a rough version in a Spreadsheet before making regular in SQL
- Ad hoc interpretations-> color coding, leaving comments, highlighting data
- Formula repetition -> easily changed = money (A1: A52) in = Average (A1: A52); The questions do not need to rewrite or verify the syntax
6. Your audience does not speak SQL
Company leaders, project managers, and outdoor clients are more likely to open the spreadsheet than the database.
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Through the spreadsheet, they find something they can read, compromised, and they intended to learn without learning the language of programming.
7. Consider your cost and access
Maintaining the relevant database in the production environment can be expensive. Think about cloud storage, computer resources, and admin -time.
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Spreadsheets are free or almost free. If your data and analysis is something that the spreadsheet can handle relatively easily, selecting it avoids the selection of the SQL.
8. You need a quick data entry
The database is not designed for easy -line row row input. You have to either write an inquiry or import data, guess what, a spreadsheet.
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It is easy to type directly to the spreadsheet if you want, for example,:
- Record Meeting Note
- Collect several leads of sales
- Track the doses or deadline
Conclusion
Of course, the best way is to combine both the Spreadsheet and the SQL. The latter is for heavy data processing, change and analysis, especially if it involves repeated work. Then it pays to establish a logical inquiry and run it back when needed. If you are just getting started or needing a refresher, it SQL cheating sheet There is a huge source for basic concepts that you will actually use.
Spreadsheets improve when you look for acne, instant understanding of data, light reviews, quick data concepts and sharing.
Net Razii A data is in a scientist and product strategy. He is also an affiliated professor of Teaching Analytics, and is the founder of Stratskrich, a platform that helps data scientists prepare for his interview with the real questions of high companies. The net carrier writes on the latest trends in the market, gives interview advice, sharing data science projects, and everything covers SQL.