Dear Eduardo

For me, I prefer Text files, if you want to use them, then, you can use the CSV format usable simply by Excel.

Good luck.

Dear Eduardo González-Fraile

Ms Access is very outdate software package.

If you want to manage datasets and logically see the relationships between them then MySQL workbench is best option.

Ms Excel also a good option but it has limited support for database related things.

I like to use Excel for data entry. It can be used to have a Worksheet for the data, a Worksheet (in the same file for the data discretionary or code book, and a third Worksheet for the actual layout of an experiment (if you are doing a scientific experiment). The layout is the randomised plots and any structural aspects of the experiment such as Blocks. he columns allow a heading for a variable and a each row is a plot or a person. So I would save this file as an Excel. The checking of data and looking for typos and mistakes should be attended to at this stage. in addition I would save a csv file of the data Worksheet. The next step is to import the data into a statistical package (my preference is R) .

The flexibility of using an object orientated program such as R allow you to do all the validation, exploratory look at the data, plotting and appropriate analysis.

This means the columns of data contain plot number, treatments, blocks, and if it is complex there should be a column for each factor.

remember to back everything up, and use good data management methods.

miranda

You can use Jamovi (jamovi.org) to enter your data directly and generate a csv file and within this nice piece of open source software, you could directly start doing your analysis and visualize the results.

Thanks a lot!!. I think in the same way. Access is outdated and there are another options more interesting.

Hello Eduardo González-Fraile,

Regarding you question Access or Excel? Which is better? What is the best tool to create a dataset?

Assuming a dataset is a collection of related sets of information that is composed of separate elements but can be manipulated as a unit by a computer; and, Better being defined as a more excellent or effective type or quality method or tool.

The unknown side of the question is are you working alone and is this a part of a repeating process to be used by others.

Personally, you can use what ever works best for you. If you are doing text manipulation for the creation of a dataset for your own work product. The question is what do you want to learn? Does it matter if things can get done better or quicker using some method already proven based off of your experiences or are you able and looking to experiment and try new methods.

Over the years I have use many methods to old to mention and still use text, Access, Excel, and SQL Server to get a job done and make it repeatable as a TSQL script. I am currently moving into R and Python as they have come into fashion.

Find mentors and others people willing to show you better ways, accept what works for one may not be the best for another, and in groups things need to be more standard.

Good Luck,

Jim Finnie

CEO Fantast Corporation

Those two pieces of software are actually tailored for different stuff. XL (and it's open software relatives like Libre Calc) are spreadsheets - simple tools to make some simple calculations in tables. Access on the other hand is a software to handle relational data bases. For simple stuff both are quite similar in operating, but as you go deeper they are completely different stuff.

The question is what is your goal? If you need to put some values into table and make some statistics, use anything that is simple and fast in this job - possibly XL, Libre Calc. If you need to handle huge dataset, with logical relations, where structure is important - go for relational databases - possibly not Access but some of the SQL flavors (PostrgreSQL, SQLite, MySQL etc.).

Further, dealing with datasets seems to by most trivial thing in the world, but it isn't. Some data scientist even joke that they spend 80% of their time on cleaning data before they even start an analysis. Thus I strongly recomend you to read a paper 'Tidy data' by Hadley Wickham about keeping proper structure of your data set (no matter how large it is). The idea had a huge impact on R community, thus if you are planning to learn R and how to manipulate data with it (it's so easy this days...) it should be your firs read. Also, the whole idea rose from Hadley's experience in relational databases, so you can treat it as easy explanation of intuition behind the logics of SQL without getting into serious programming stuff.

Last but not least - small correction of what Miranda wrote - R is actualy not an object oriented language, but functional language. Of course it also implements object paradigm, but it's main advantage for data scientists is that it's primary functional. For data scientist not interested in programming the difference between functional and object is not especially interesting, but later as you gain more expertise you will wonder who the hell is using object oriented style while programming in R ;)

Hope that helps.

@Eduardo González-Fraile

What I proposed you is to use something simple and easy to create and use your data. However, Excel and Access are two different things and not outdated.

Excel is for managing spreadsheets (tables),

Access if for managing data as a database (it could also handle tables)

So, you have to know that to generate and manage a csv file you could start using even a text editor (yeah the simplest one is enough) or a dev editor (like vscode, atom, ...), in these cases it would be hard, if you lack experience, to manage more than 5 columns and 50 rows, so it would be nicer and easier to do it in a visual condition (like in excel, libre calc, google spreadsheet, access, jamovi, jasp, ....).

Sorry if I insist, but there is rarely things that are outdated, the strength of a tool or software is within its user not in how many functionalities they gather. I hope you will learn to use some tools to the extent that you will enjoy producing and managing your data without following fashion.

In brief, Excel is better for small, non-relational datasets. i.e if your dataset is a single table with less than 100,000 records, then use Excel.

If your dataset is relational (two or more tables related to each other, like customers/products/sales tables, or if you have large number of records, then Access is better.

For my advice, if you know some programming skills, go for pandas, the python package for analysis, it is better than both, it deals with all formats (especially CSVs), and have capabilities of pivoting, grouping, and even graphing.

I agree with Mohammad N. Elnesr -- you are better off going with R or Python because working with a script makes it easier to import, clean, manipulate and summarize your dataset in a reproducible way.

Whatever you say, I do everything I need using Excel.

Excel is suggested for single ( simple dataset) and ACEES for relationnals data tables