Data Access

1. Data access

Now that you are familiar with the tool, it's time to explore some more data. But first, you need to know how to access it.

2. Data access

Accessing data means reading its content into a data table that can be processed in the workflow. Data can come from different sources. It could be a file stored on your laptop or stored on the cloud, a database or big data table, or even the result of a REST API request. In all those cases, accessing those data just means copying its content to the workflow. The original source is left unaltered. KNIME Analytics Platform offers many ways to access your data by providing a wide number of reader nodes.

3. Data access

For example, in the previous chapter, you have already accessed the Excel file with the Excel Reader node.

4. File types

Similarly, you can read other file types on your machine with the relative reader nodes. Don't be overwhelmed; you will find the correct reader nodes easily.

5. File path

Once you get the right reader node, you must specify a file path. Imagine the file system as a maze and the file as the prize. The file path are the instructions to navigate the maze and get to the prize. On your local file system, those instructions can be absolute or relative.

6. Absolute file path

Absolute paths always start from the entrance of the maze - in this case, the root of your file system.

7. Relative file path

Relative paths, on the other hand, describe the route starting from a known landmark, most commonly your local workspace or your current workflow. The advantage is that the relative path will still be valid if the workflow is executed on another machine.

8. Connected file systems

What if the data you want to read is not saved on your machine but in a remote location? In those cases, we talk about a connected file system. Examples are Google Drive, Microsoft Sharepoint, Box, or even your company's internal server. To access files in those file systems, you need to authenticate and connect to them with the dedicated nodes.

9. Connected file systems

The connector nodes act like a plugin to the reader nodes. Once you provide the connection, you are able to browse the remote file system and select the file that you want to read.

10. Multiple files

Simple so far: you add a node, and you read a file. The HR department that asked for your help, however, informs you that their data is scattered over 20 different Excel files. Does this mean adding 20 reader nodes, one for each of them?

11. Reading folders

Of course not. KNIME Analytics Platform can also access all the files in a folder at once and concatenate all the content in a single table.

12. Accessing Databases

Finally, you can also access data in a database with the dedicated nodes. Reading data from a database is called querying. A query is an instruction to tell a database which data you want to read. Queries should be written in a specific language, such as SQL. Writing database queries goes beyond the scope of this course, but you must know that with KNIME Analytics Platform, you can query a database without writing the query itself. You only need to connect to the database and use the nodes to build and execute the query.

13. Let's practice!

Now you know different ways of accessing data - let's test what you've learned!

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