Load Your Data

Nothing in Keboola happens until there is data in Storage. This step puts four tables there by uploading CSV files by hand — the fastest way to get something real to work with. Step 2 of the Getting Started arc.

What you need

• A Keboola project you can sign in to. If you do not have one, start with Get a Project.
• The four sample files below, downloaded to your computer.

The sample data

Four small tables describing a sales pipeline: opportunities, the accounts they belong to, the users who own them, and each user’s seniority level.

• opportunity.csv — business opportunities
• account.csv — the accounts
• user.csv — the users
• level.csv — company levels per user

Download all four before you start. All characters in this data are fictitious, and any resemblance to real persons, living, dead, undead, unborn, or otherwise semi-existent is purely coincidental.

Two ways data gets in

Keboola loads data with data source connectors — components that pull from a source on demand or on a schedule. One of them, CSV Import, simply takes a file you upload.

Manual upload is the right tool when you are starting a project or proving something out. For production you move to a connector that talks to the real source: a database, an API, a cloud drive. This step uses CSV Import; the two side trips at the end of this page do the same job with a Google Sheet and a database.

Load the first table

1. Open Components and search for CSV Import.

   

2. Click Add Component, then Connect To My Data.

   

3. Name the configuration [TUTORIAL] Opportunity, add a description, and click Create Configuration.

   

   One connector can hold many configurations — you will create four here, one per file. Clear names and descriptions are what keep a project readable six months later; see the best practices cheat sheet for conventions.

4. In the CSV File section, click Select file and pick the opportunity.csv you downloaded.

   

5. In Upload Settings, click the pen icon next to Destination. The destination is three separate controls, not one string:

   Control	Set it to	Why
   Stage	IN	data arriving in the project
   Bucket	csv-import	already the default
   Table name	opportunity	the only one you need to change

   Click Save. Together they make the table’s full Storage ID, in.c-csv-import.opportunity — the name the next step’s SQL refers to. (Storage adds the c- prefix to bucket names itself.)

   

6. Click Upload.

   

Load the other three

Go back to Components and repeat steps 1–6 for the remaining files, changing the configuration name and the table name each time:

File	Configuration name	Table name	Full Storage ID
account.csv	[TUTORIAL] Account	account	in.c-csv-import.account
user.csv	[TUTORIAL] User	user	in.c-csv-import.user
level.csv	[TUTORIAL] Level	level	in.c-csv-import.level

The destination names matter: the transformation in the next step refers to these exact tables.

Check it worked

Open Storage. Data is organized into buckets, and each bucket holds tables. You should see one bucket — listed as csv-import with an IN badge, its full ID being in.c-csv-import — containing four tables:

Click a table name to see its columns, row count and a Data Sample of the actual contents. If the sample looks like your CSV, this step is done.

If it goes wrong

• The upload job fails. Open Jobs and read the job’s log — for CSV Import the usual cause is a delimiter or encoding mismatch. The files above are comma-separated UTF-8.
• The table lands somewhere unexpected. The destination was left at its default. Edit the configuration’s Upload Settings, fix the destination, and upload again; the wrongly named table can be deleted in Storage.
• Every row arrives as a single column. The file was saved with semicolons by a spreadsheet app. Re-download the original, or set the delimiter in the configuration.
• Nothing happens when you click Upload. The file selection did not stick — reselect the file, save the configuration, then upload.

Or ask Kai

Kai can inspect what landed and tell you whether it looks right:

List the tables in the in.c-csv-import bucket with their row counts, and show me a sample of opportunity.

Going further

• Load from Google Sheets — the same data pulled from a spreadsheet automatically instead of uploaded by hand.
• Load from a database — the pattern every database connector follows.

Next: Transform your data →