We’ll create a query called LateDeliveriesByOrigin. We’re basically going to get the same information as our previous query, but this time we’ll group it by source rather than my date:

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But, we want to do a little bit of formatting. We’ll use some custom JavaScript for the first two because we want to round our figures to two decimal places.

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Next, we want to build a very similar dashboard screen for data relating to our deliveries. We’ll start by duplicating what we have so far.

For our last card, things are a bit more complicated. We want to display how much we’ve spent on fuel for the current month so far.

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Our label column is vehicle and the data column is average_cost_per_mile. We’ll also select the horizontal option and apply some similar custom CSS to what we did for our pie chart.

The first thing we’re going to do is create a new Budibase application and give it a name. We have the option of starting with a template or importing an existing app, but we’re starting from scratch:

For our pie chart and bar chart, we’re going to display the number of deliveries that have departed from each of our sites.

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Inside this, we’ll place four cards blocks. Each of these will iterate over a specific data set and display whichever values from each entry that we want them to.

Now, we can go back and swap out our values for these without much fuss - we just need to filter for the month and year again - using the same JavaScript binding as we did earlier:

Fleet management dashboards are reporting UIs that display key metrics and KPIs relating to various aspects of how we use our vehicles.

We’ll start with a new query called FuelCostByVehicle. This one is relatively simple. We just need the average of (fuel_cost over miles), grouped by vehicle.

For the month, we’ll use this piece of JavaScript (we need to add one because JavaScript uses zero-based counting - so January has an index of 0:

Our fleet management dashboard is built around two thematic reports - one for insights into our vehicles themselves - and one for their performance on deliveries.

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Straight away, we’ll be prompted to choose our data source. Budibase offers dedicated connectors for a huge array of relational and non-relational databases, as well as REST, Google Sheets, and our own internal DB.

The fourth card is a bit trickier. Our query will return a positive or negative number depending on whether we’re ahead or behind schedule. We want to display a positive number no matter what and then alter the subtitle to indicate if we’re ahead or behind on average.

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Lastly, we want to make some space for the other chart, so we’ve added some custom CSS to set the chart’s width to 50% and fix its height at 400px. We’ve also given it a descriptive title:

Since this is for the current month only, we’ll use a bit of JavaScript to reflect this fact in the title, using the expression:

Our query returns multiple data objects. So, we need one final step to add some front-end filtering so that we only see the current month’s figures.

So, we basically need a query that finds the row for each vehicle with the most recent arrival_date - and then counts the vehicles at each location based on this.

We hope you found this tutorial helpful. To find out more about how Budibase empowers teams to turn data into action, check out our features overview .

We’ll start by giving our first three cards more descriptive names and setting their data to our new query. Now each one only displays one card - because it only iterates over a single object:

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Each one has a title, subtitle, and description field. We’ll set the title to be each of the respective figures - and the subtitle as some text to explain what this is.

We want this chart to occupy half of the screen - and later we’ll put another graph beside it - so we’ll start by adding another horizontal container:

If you cast your mind back to our finished dashboard from earlier, the four metrics we’re going to display in these cards are:

We can set a custom color code for our options, but if we don’t then Budibase will do this for us. Here’s what our table looks like now:

We want our summary cards on this page of our fleet management dashboard to display the following metrics for the current month:

We need two expressions - one to match the departure_month to the current month and another to do the same for the departure_year.

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Ultimately we’ll select the same count of deliveries and count of late deliveries as we have in the last couple of queries. We also have one extra statement that prevents us from getting a zero division error.

We’re going to build our dashboard around data that lives in a Postgres database. When we select this, we’re prompted to enter our database credentials. Users on paid tiers can use environment variables to store these and leverage them across their Budibase apps.

We’ll also edit the status attribute and choose the options type, rather than keeping it as a text field. We’ll input the three possible values - On Delivery, Idle, and Maintenance:

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As with any kind of dashboard, the idea is that we can configure our reports once - and then they’ll populate with the most up-to-date information in real-time.

This can include things like where our assets are, how much we’re spending on fuel, our performance in terms of deliveries, statistics around our overall vehicle utilization, driver safety, or any other relevant data that decision-makers might need.

Budibase gives us two different ways to bind values to a field - handlebar expressions or JavaScript. If we were happy with the format of our data as it’s returned by our query, we could just select plain handlebars:

At the top of our fleet management dashboard, we’ve got a series of cards that read out key statistics about the current state of our fleet.

Now - what we want to do is work through each of our charts and swap out their data to display metrics that are relevant to our fleet’s performance.

As we’ll see, Budibase is the ideal tool for extracting insights from all kinds of data sources and turning them into clear, actionable insights - so we can make better-informed decisions.

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So, for the title, we check if the time difference is positive or negative. If it’s positive, we return it as is. If it’s negative, we multiply it by -1 before we return it:

And we’ll set the subtitle to average vehicle age. We’ll also do basically the same thing with our next card, using our average_mileage output from the query.

Again, this is a slightly more complex query - because our vehicles table doesn’t have a column for their current location. However, we can figure out the last location where each one made a delivery.

So, we need to use the same WITH statement we did earlier to generate a series for each day this month and use a JOIN statement to match this up with data from our table.

Our fleet management dashboard will be mainly built around custom Postgres queries, but we’re still going to make a few changes to our data tables for the sake of house keeping.

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To get this, we’ll first need a new query to SELECT the numerical month, year, and SUM of the fuel costs - grouped and ordered by month and year.

We’ll make some similar changes to our deliveries table - setting the id attribute as our display column and changing the origin and destination fields to the options type.

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We’ll first create a series of all of the days so far this month. We’ll then use a COALESCE statement to SUM our fuel_cost attributes - but return 0 on the rows where this is NULL - and LEFT JOIN this to our series.

For our utilization rate, we can just display an integer with a percentage sign appended to it. To do this, we’ll use the following handlebars expression as our title binding:

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Lastly, we’re going to make a couple of little design tweaks. First of all, we’ll head to the theme tab and select Nord to give our dashboard a slightly different feel: