WEBVTT 00:00.880 --> 00:01.800 Welcome back. 00:01.840 --> 00:08.840 In this lesson, we are breaking down how Nathan handles data so you can build cleaner, more efficient 00:08.840 --> 00:09.600 workflows. 00:10.000 --> 00:18.480 By the end of this video, you will understand how Nathan structures data with JSON and lists how nodes 00:18.600 --> 00:24.640 process and parse data, and how to use expressions to modify and work with that data. 00:25.120 --> 00:27.040 So let's get straight into it. 00:33.480 --> 00:33.960 All right. 00:33.960 --> 00:35.560 So let's start with the basics. 00:36.160 --> 00:44.920 Nathan processes everything in JSON, which is just a fancy way of saying data is stored in key value 00:45.400 --> 00:46.040 pairs. 00:47.160 --> 00:51.080 So for example a JSON object might look like this. 00:52.720 --> 00:56.880 You have a key and value key and corresponding value. 00:58.960 --> 01:00.000 Easy enough right. 01:00.400 --> 01:03.640 So now what if you have multiple records. 01:04.690 --> 01:06.450 That's where lists come in. 01:07.370 --> 01:11.970 Because a list is just a collection of multiple JSON objects. 01:13.170 --> 01:16.730 So this is one list of two JSON objects. 01:18.610 --> 01:22.250 So think of it like rows in a spreadsheet. 01:22.890 --> 01:25.650 Each JSON object is a row of data. 01:26.290 --> 01:29.490 This is how an A-10 handles multiple items at once. 01:33.410 --> 01:36.730 So how do nodes actually handle this data? 01:37.090 --> 01:43.410 Each JSON object is called an item, and nodes process one item at a time. 01:43.890 --> 01:49.010 So let's say we have three dates to format a date and time. 01:49.050 --> 01:54.730 Node will process each item separately so it runs three times once per item. 01:56.570 --> 02:04.610 So if an if node checks for customer with a Gmail email, it will process each email individually and 02:04.610 --> 02:07.090 only pass through the ones that match. 02:08.990 --> 02:15.190 And the best practice is to always keep in mind how many items your note is processing. 02:15.430 --> 02:18.550 So this is super important when building workflows. 02:20.230 --> 02:24.590 Now fix fields versus expression fields. 02:25.430 --> 02:32.550 So when filling out fields in return you might notice some fields behave differently because there are 02:32.830 --> 02:35.230 fixed fields which always stay the same. 02:35.510 --> 02:40.350 And expression fields which dynamically change based on input data. 02:40.870 --> 02:47.590 So let's say you are sending an email and you could set the subject to welcome to our service. 02:48.750 --> 02:59.990 So this is this will always be the same while expression subject welcome and then JSON object. 03:00.990 --> 03:03.070 This adapts based on user data. 03:03.630 --> 03:09.390 So if a field allows expressions you will see the little f button. 03:11.150 --> 03:15.720 And you need to click to switch between fixed and dynamic values. 03:17.840 --> 03:23.600 Best practice is always to use expressions if the data is different for each item. 03:24.280 --> 03:33.840 So you can dynamically input data so you don't need to hard code your data like provide the actual name 03:33.840 --> 03:34.800 of the user. 03:34.960 --> 03:41.280 You can just use JSON object and the correct name will be passed into field. 03:41.880 --> 03:47.480 We will explore this topic on practical examples in N810, so don't worry. 03:49.840 --> 03:51.640 Now let's talk about expressions. 03:53.880 --> 03:57.160 So we use expressions to access and modify data. 03:59.320 --> 04:03.800 This is how you access, modify and format data dynamically. 04:06.560 --> 04:09.640 So for example you want to grab a customer's email. 04:10.520 --> 04:12.240 You need to use this expression. 04:13.640 --> 04:19.370 But if you need to combine a first and last name, you can easily do it using expression. 04:20.930 --> 04:27.130 Now the best practice is to use expressions to reference and format data dynamically. 04:29.210 --> 04:35.410 So instead of hard coding values, your workflow always works with real time data. 04:37.810 --> 04:43.570 Now next we have data transformation with set function and code nodes. 04:44.970 --> 04:50.010 Now what if you need to modify data before passing it to another node? 04:50.490 --> 04:52.850 In N810 you have three main tools. 04:53.810 --> 05:00.210 Head node which is great for renaming, removing or adding simple fields. 05:00.850 --> 05:06.410 Function node lets you write small JavaScript snippets and code. 05:06.450 --> 05:09.090 Node when you need to. 05:10.010 --> 05:15.770 When you need more advanced transformations to handle complex logic, which is not possible in expressions. 05:16.450 --> 05:19.950 For example, you want to convert a name to uppercase. 05:20.870 --> 05:23.950 So you use expression the function node alternative. 05:24.150 --> 05:27.670 Looks like that which is written in JavaScript language. 05:31.870 --> 05:38.110 And the best practice is always use the simplest method first and only use code when it's necessary. 05:38.750 --> 05:45.630 And there is no many use cases where you have to use code to build powerful automations and agents. 05:48.910 --> 05:49.350 All right. 05:49.350 --> 05:52.190 So now let's talk about nested JSON data. 05:52.750 --> 05:56.990 This comes up a lot when working with APIs and databases. 05:57.270 --> 06:03.710 So sometimes instead of simple key value pairs you will get objects inside objects. 06:04.670 --> 06:13.430 As you can see we have object name inside user object which you can notice thanks to indentation. 06:14.790 --> 06:23.560 If you try JSON email, it won't work because the email is inside user contact object. 06:24.920 --> 06:28.000 So instead you need to reference it properly. 06:28.560 --> 06:32.160 So JSON dot user dot contact dot email. 06:33.040 --> 06:36.960 Best practice is if you are dealing with deeply nested data. 06:37.200 --> 06:40.800 Use a set node to restructure it first. 06:41.600 --> 06:44.600 So how does this all work together in real workflow? 06:47.320 --> 06:51.880 Pulling the trigger like a webhook or manual trigger to start the workflow. 06:52.520 --> 06:55.600 Then data retrieval. 06:56.320 --> 07:02.480 So to fetch the data you need, you need data retrieval node like Google Sheets. 07:03.360 --> 07:04.520 Then processing. 07:05.560 --> 07:12.440 So the data gets modified, filtered or formatted and finally output. 07:12.720 --> 07:17.960 So the processed data gets sent to another tool or system like slack. 07:19.440 --> 07:27.770 Let's say you pull data from Google Sheets and if it returns three rows and if not, filter out one 07:27.770 --> 07:31.090 row, leaving only two rows for the next step. 07:31.890 --> 07:36.010 To pass this data to pass these two rows to slack. 07:37.250 --> 07:44.170 So this is why understanding how naa10 processes items is is key, because each step transforms the 07:44.170 --> 07:49.250 data before it moves, before it moves to the next node. 07:52.490 --> 07:55.490 Now understanding input and output of nodes. 07:55.970 --> 08:02.930 So if a node is not working the way you expect, the issue is usually the input format. 08:03.370 --> 08:06.810 So every node expects data in a specific structure. 08:07.090 --> 08:12.410 So if it doesn't match you might get errors or unexpected results. 08:12.930 --> 08:19.090 So for example you call an API and it returns this JSON. 08:22.050 --> 08:30.730 But your next node is looking for JSON email which doesn't exist at this level because your email. 08:32.150 --> 08:34.550 is in data JSON object. 08:35.910 --> 08:40.550 So to fix it you need to add the reference. 08:40.990 --> 08:44.310 So body dot data dot email. 08:45.470 --> 08:48.470 The best practice is if something is not working. 08:48.470 --> 08:51.830 Always check the execution data of the previous node. 08:52.270 --> 08:56.190 So that will show you exactly what's being passed. 09:00.910 --> 09:02.470 Now why this matters. 09:02.830 --> 09:12.030 So understanding how attend processes data helps you avoid workflow errors when handling multiple items. 09:14.390 --> 09:18.230 It makes your automations faster and more efficient. 09:18.630 --> 09:25.670 And once you get comfortable with expressions and data handling, you can build way more powerful workflows. 09:26.070 --> 09:31.430 So if you ever get stuck with inputs, outputs, or expressions, come back to this lesson. 09:31.950 --> 09:34.590 I hope this was helpful and see you in the next one.