Matt Fairbrass

2 results

Exploring New Security, Billing, and Customization Features in Atlas Charts

MongoDB is excited to announce a few new updates to Atlas Charts that enable you to securely share insights, gain deeper visibility into expenses, and customize your most frequently used data visualizations. Based on specific feedback received from users of our native visualization tool, these significant improvements will make data analysis even more productive. We: Improved security in Atlas Charts for passcode-protected public dashboards Increased visibility into Atlas spending through an updated billing dashboard Introduced new customization for table charts through hyperlinks and hidden columns Secure insights with passcode-protected public dashboards First, there’s the new passcode-protected public dashboards feature that brings an extra layer of security to publicly shared dashboards—we understand that not everyone who benefits from Atlas Charts operates within MongoDB Atlas. Alongside the ability to schedule email reports and support for publicly-shared dashboards , we’re offering a new and secure way to spread insights with the launch of our latest feature. Add an extra layer of security to previously publicly shared dashboards, ensuring that only authorized users with the passcode can access your data. Enabling passcode protection on a dashboard is simple. As a dashboard owner, a new option is available to protect dashboard links with a passcode when sharing it publicly. Check the box to protect your public link with a passcode Once enabled, a passcode is automatically generated and can be copied to the clipboard (and regenerated on demand as needed). Viewers navigating to dashboards via the public link will see a new screen prompting them to enter a passcode. Once authenticated successfully, they can view the dashboard just as before. Easily access your dashboards by inputting your password when prompted Whether you're sharing insights with clients, stakeholders, or team members, rest assured that your data remains easily accessible yet secure. To learn more about the different ways we support dashboard sharing, check out our documentation . What’s new in the Atlas Charts billing dashboard Next, we continue to make enhancements to the MongoDB Atlas Charts billing dashboard , all of which provide insights into Atlas expenses. We are delighted to share that it’s now possible to see resource tags data, as well as billing data from all linked organizations inside the Atlas Charts billing dashboard. Additionally, users can now ingest billing data from another organization, provided they possess the organization’s API keys. These newly introduced features rely on the availability of billing data within the organization. And for those leveraging resource tags, the billing data will seamlessly integrate, empowering users to generate personalized charts or to incorporate tailored dashboard filters within the Atlas Charts billing dashboard. If cross-organization billing is enabled, editing the configuration will ingest the linked organization’s billing data for the last three months, with the option to extend this period to up to a year by creating a new ingestion. Project tags data in the Atlas Charts billing dashboard Resource tags are now seamlessly integrated into billing data and can be included in any of the charts or the dashboard filters inside the Atlas billing dashboard. For example, our MongoDB organization uses the Atlas auto-suggested tags “application” and “environment,” alongside a custom resource tag labeled "team." The following chart uses the tags data and shows the billing cost per team and per environment. A chart which depicts cost per team and environment using tags The subsequent chart presents the billing cost allocated per project and team, providing valuable insights into the primary cost drivers for each team's projects. A chart depicting cost allocated per project and team Users can also add a dashboard filter to the “tags” field, which will allow them to see the whole dashboard based on the selected tag values. In the next example, we have selected a specific “team” : “Charts” from the tags dashboard filter, so we can see all of the billing insights per team thanks to our custom tag. Billing insights filtered by specific "charts" team in an intuitive dashboard Linked organization’s data in the Atlas Charts billing dashboard For complex Atlas projects spanning multiple organizations, the Atlas Charts billing dashboard now seamlessly integrates billing data from all linked organizations. The most productive use case is to add a dashboard filter based on the "organizationId" to enable filtering data according to specific organizations for a more granular analysis of the spending. Dashboard filtered by the organizationID field to show insights for one organization Billing data from another organization Users can now ingest billing data from other organizations that are not directly linked, provided they possess authorization API keys, bringing the data you need to where you are. Provide the API key to ingest billing data from other organizations These new features in the Atlas Charts billing dashboard are designed to provide richer, more detailed insights into organization spend. Check out our documentation and our previous blog post to learn more about it. Hyperlinks and hidden columns for tables in Atlas Charts Of all the data visualization methods available in Atlas Charts, table charts rank as one of the most popular among our users. So it should come as no surprise that one of the most highly requested features from our customers is the ability to format columnar data as hyperlinks. We're excited to announce that this is now possible in Atlas Charts through the new hyperlink customization options available for table charts . With hyperlink customization, you can format columnar data as hyperlinks using any of the following URI protocols: http, https, mailto, or tel, and can be constructed statically or dynamically using encoded fields. Let’s assume we’ve created a table using the sample movies dataset in Atlas, with encodings like title, imdb.id, runtime, genre, poster_display—which is a calculated field —and more. Customization panel in Atlas Charts To turn movie titles into clickable links that direct users to their respective IMDB pages, navigate to the customization panel and click into the hyperlinking feature in the fields tab . We will format the title field as a hyperlink which links to the Internet Movie Database (IMDB) entry for that movie. IMDB URLs are formatted as follows, where id needs to be substituted with the value of the imdb.id field for each document. https://www.imdb.com/title/tt<id>/ Customize the “title” field in the table chart to link to IMDB using the “imdb.id” field in the URI input. Below, a preview displays the fully formatted URI with fields substituted for their values, helping to ensure it’s correct before we save it to be applied to the chart. Preview of URI in the hyperlinking panel Since we only need the imdb.id field to be encoded for the purpose of constructing the URI applied to the title field, we can hide the column from rendering using another new customization option. Select the imdb.id field in the customization panel, and toggle on the “Hide Column” option. Toggle "Hide Column" We also support using URI values directly from fields (provided they use one of the supported protocols). Let’s see this in action by creating a hyperlink to the movie poster. In the URI input, trigger the encoded field menu using the @ keyboard shortcut, and select the poster field. Similar to the previous example, a preview will be displayed. After saving and applying the hyperlink formatting, we can hide the rendering of the poster field as needed to keep the chart clean. Use the @ keyboard shortcut to trigger the encoded field menu All these options are accessible in the customization panel, making it straightforward to enhance table charts with interactive hyperlinks. For more detailed instructions, visit our documentation . As we conclude this roundup, we hope you’re as excited about these updates as we are. The Atlas Charts team is dedicated to continuously improving Atlas Charts to meet your needs and enhance your data visualization experience. Stay tuned for more updates, and happy charting! New to Atlas Charts? Get started today by logging into or signing up for MongoDB Atlas , deploying or selecting a cluster, and activating Charts for free.

September 5, 2024

Distinguish Data, Get Insights Faster with Conditional Formatting in Charts

The latest release of MongoDB Charts adds Conditional Formatting; an exciting new feature that enables chart authors to highlight important changes in their chart data, based on a set of rules that they define. Conditional Formatting rules can be applied to table charts and number charts . Why use Conditional Formatting? For table charts, the data is densely packed into the visualisation using rows and columns. This is great for comparing many values simultaneously, but as the density increases it may become more difficult to find and focus on the data that matters. Many authors use Number charts to track key individual metrics within their data. While the number itself can be useful, sometimes it isn’t enough to convey other necessary information for its context – for instance, is a high number good or bad? Conditional Formatting can aid users in understanding the data by applying different styles based on rules to highlight what is important, and to provide them with more context. See Conditional Formatting in Action with Formula 1 Data Formula 1 motorsport is what I like to refer to as the “sport of nerds”, because analyzing and understanding huge amounts of data, and being able to quickly make a decision on that analysis can be the difference between winning and losing. So let’s see how Conditional Formatting can help with this task using data from the 2021 FIA Formula 1 World Championship. Single Color Conditional Formatting Let’s start off with something simple. Below is a table showing the 2021 Drivers Championship after three rounds. A driver’s position in the championship is determined by the total number of points they have been awarded over successive rounds of the season. Let’s edit this chart and add Conditional Formatting to highlight the top three drivers in the championship with colors to represent 1st, 2nd, and 3rd place. Click on the Customize tab , and then click on the Conditional Formatting menu to expand the accordion. As you can see we haven’t yet defined any rules, so let’s add a new rule by clicking the + Add button. A drawer will open up from the left hand side of the screen displaying the Add Format Rules view. A conditional formatting rule must have at least one condition, and all conditions must match in order for the rule to be applied. Let’s highlight the row of the driver currently in 1st place by adding a single color rule with one condition. Since this rule will be determined by the driver’s current position in the championship, we need to add a condition to act on this data. We can target this field by selecting Pos from the Applies to select control. Now that we know what field we are targeting, we must next choose an operator to use for the comparison. Since we are only interested in data that matches a specific value, we select the Equal To numeric operator. Next we must provide an input for the operand to be compared to. For this rule we are only interested in highlighting the driver that is in first place in the championship, so we enter a value of 1 into the Input . You can think of this condition as saying; “is the value of the field Pos equal to the value of 1?” If it is, then apply the styling of this rule, otherwise do not. Finally we choose what styling changes should be applied by choosing from the options under Styling . In this example, we want to highlight the background color of the cell in a gold color to signify 1st place, and we will also apply a bold font weight to the text to make it more prominent. Additionally we also would like for these styles to be applied to the entire row, and not just the cell that the condition is applicable to, so we will check the Format entire row option. And that’s it! Once we save the rule, you’ll notice that the table re-renders in the Chart Builder Preview to show that the data is being evaluated correctly and the Conditional Formatting rule is applied. We then simply rinse and repeat this process to add additional rules to highlight the drivers in 2nd and 3rd place, resulting in the following output: Color Scale Conditional Formatting When comparing tabular data, sometimes it is desirable to use color to show where each value lies relative to other values in the column. The table below shows the race results for the third round of the 2021 FIA Formula 1 World Championship. Each row displays the final result for each driver taking part in the race. Let’s compare the Average Speed of each driver’s Fastest Lap using a Color Scale Conditional Formatting rule. Navigate to the Add Format Rule screen in the same way by going to “Customize > Conditional Formatting > + Add” , but this time select the Color Scale radio option. Note: Conditional Formatting Color Scale rules can only have one condition, and this condition can only be applied to fields in a Table Chart encoded as Value columns. Select the Fastest Lap Average Speed as the target for the condition. You’ll notice that unlike the discrete Single Color rules, there are no other settings to configure for the condition. This is because a Color Scale will compare the values across the documents in sort order, and will determine a background color to apply to the cell based on the rank of the value within the range. Since we are interested in finding the highest Average Speed across each driver’s fastest lap, we will select a sequential color scale, where higher values are colored green, and lower values are colored in white. Save the rule to see the changes applied. As you can see, for the third round of the 2021 FIA Formula 1 World Championship, the fastest lap average speed was set by Valtteri Bottas at a blistering speed of 209.74 km/h (130.32 mph)! And there we have it. I hope this brief introduction to Conditional Formatting has highlighted (pun intended) the capabilities of this exciting new feature! In this post we’ve only scratched the surface of what’s possible though, Conditional Formatting has many many more powerful operators than what we have demonstrated here, including matching values by range, regular expression and even ranks. Why not take it for a test drive yourself to see what is possible? If you haven’t tried Charts yet, it’s quick, easy and free to get started. Simply sign up for MongoDB Cloud , deploy a free Atlas cluster and click Charts in the top navigation bar. You can also ask questions on the MongoDB Developer Community Forums , or suggest new or improved features using the MongoDB Feedback Engine .

May 13, 2021