Atlas Charts

52 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

Introducing AI-Powered Natural Language Mode in Atlas Charts

At MongoDB, our mission is to empower developers to seamlessly and efficiently build modern applications. To that end, we’ve announced a number of tools and improvements to help developers build faster , from AI-powered SQL query conversion in Relational Migrator to the MongoDB Provider for Entity Core Framework. In the same spirit, today at MongoDB.local Sydney we’re excited to announce the general availability of Natural Language Mode in Atlas Charts . Not only does this release help developers move faster with AI, it also showcases the work of MongoDB’s nimble Sydney engineering team. Intelligent developer experiences: The next level of productivity Over the past year, we’ve introduced a range of intelligent developer experiences across our platform, all of which aim to simplify and accelerate development processes. Overall, our goal is to make tools faster, better, and more connected for our developers, and to enable developers to leverage the power of AI to enhance their experience. As IBM highlights , true developer productivity involves delivering high-quality outputs that satisfy customers but also avoid developer burnout. By reducing learning curves, saving time, and providing easily accessible insights, intelligent features enable developers to focus on their most important work: building modern applications that solve real-world problems through outputs that are truly worth developers’ time and effort. Here’s what we’ve introduced: MongoDB Compass —Developers can use natural language to compose everything from simple queries to sophisticated, multi-stage aggregations. MongoDB Relational Migrator —With natural language, developers can convert SQL queries to MongoDB Query API syntax, streamlining migration projects. MongoDB Documentation —An intelligent chatbot, built on top of MongoDB Atlas and Atlas Vector Search, enables lightning-fast information discovery and troubleshooting during software development. By integrating AI into our most important developer tools, we’re helping developers cut through the noise and focus on creating innovative solutions. Simplifying data visualization with Natural language Mode Visualizing data can be an incredibly effective way of gleaning insights from application data, but creating effective visualizations can require specialized knowledge and experience with business intelligence (BI) tools. Atlas Charts was built to level the playing field. Now, with Natural Language Mode, developers can create visualizations simply by asking questions in plain English. Natural Language Mode reduces technical barriers and makes data visualization accessible to anyone with data in MongoDB Atlas. This means faster chart creation at an advanced scale—all within the Atlas ecosystem. Since announcing its development in the fall of 2023, we’ve made significant enhancements to Natural Language Mode, including an expanded suite of chart types built for all kinds of data from patient records to financial trading flows. We’ve also improved performance to ensure faster and more accurate chart generation, including the ability to handle more sophisticated prompts, filtering, sorting, binning, and limiting. In the next few weeks, we will add more chart variation, as well as another upgrade to our model that will increase accuracy and responsiveness by up to 50%. Natural Language Mode in action Now let’s walk through a few examples of what using Natural Language Mode in an Atlas Charts looks like: Generating a chart using Natural Language Mode With a simple query like "Show me the sales performance by country and product for Q4 FY2023," developers can instantly generate a relevant chart. Customizing charts in Classic Mode After generating a chart, developers can pull it into Classic Mode to fine-tune and customize it to fit their dashboard needs. Scheduling Dashboards Developers can also schedule their dashboards to be shared via email, ensuring that key stakeholders receive up-to-date insights automatically. More data, more insights Customers are already excited about the possibilities of Atlas Charts and Natural Language Mode, from operational analytics to embedded analytics. For example, one of MongoDB’s early customers has been using Natural Language Mode to track server performance across various regions. Business analysts leverage the feature to gain insights into server performance and share these insights internally. They plan to embed these visualizations into their customer portal using the embedding SDK offered by Atlas Charts . Another customer said: "As a developer with no prior experience in analytics, I was excited to see Natural Language Mode generate a clear value proposition that showcased what the product is capable of. It makes me want to throw more data in the database to get more insights." So check out Natural Language Mode in Atlas Charts today, and experience firsthand how AI can simplify and accelerate your data visualization workflows. Try out Natural Language Mode in Atlas Charts to transform your data visualization process. New to Charts? Register for MongoDB Atlas , deploy a cluster, and activate Charts for free.

July 29, 2024

Create and Customize your Own Billing Dashboard with Atlas Charts

When it comes to managing tech stacks, controlling expenses is a top priority for our customers. This summer, we've made it easier than ever to optimize your spend with new ways for visualizing and analyzing your Atlas billing data. Through Cost Explorer , you can conveniently analyze your billing data right within the Billing section of the Atlas UI. But that's not all! We know many of you prefer to craft your own Atlas billing dashboards – allowing you to customize, embed, and share tailor-made charts to align with your optimization strategies. With the latest release of Atlas Charts , we’ve made this easier than ever with a new out-of-the-box billing dashboard! Gone are the days of navigating to a Github repository , running scripts from your command line and manually importing a dashboard to gain insights into your Atlas bill. We understand the importance of quickly accessing and being able to answer questions about your Atlas spending, so we’ve made it a top priority to enhance your user experience by streamlining this process. Now, when you enter Charts, you’ll find a dedicated Ingestions page conveniently located in the left navigation menu. Here, you can effortlessly set up your scheduled billing data ingestion by entering your Organization API keys (or create them up following the steps we’ve included), and selecting the deployment and database where you’d like your data to live. Once you’ve completed the configuration and hit Save , your first ingestion job will be kicked off. Fresh data will be retrieved from the Atlas Billing API once a day to ensure the data in your nominated database is always up-to-date. After this initial job is complete, you can click Add and open to explore your new billing dashboard. Just like any other dashboard, you have the flexibility to filter and highlight charts within the billing dashboard, and customize or add new ones to tailor the dashboard to your specific needs. You could even share the billing dashboard with your team or schedule regular dashboard reports to be sent to your email. You have the freedom to manage your ingestion configuration at any time from the Ingestions page, whether you need to update your API key pair or change the database in which your data is stored. To learn more about visualizing your billing data in Atlas Charts, be sure to check out our documentation . We’re always listening to feature requests that will enhance using Charts across teams, so if you have any requests or feedback, please share them with us here . 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.

October 12, 2023

New Intelligent Developer Experiences for Compass, Atlas Charts, Relational Migrator, and Docs

This post is also available in: Deutsch , Français , Español , Português , 日本 . Today, MongoDB announced a range of innovations in its developer data platform, creating new, intelligent developer experiences in familiar tools like MongoDB Compass, Atlas Charts, Relational Migrator, and MongoDB Documentation that radically simplify and accelerate how developers build modern applications. These new experiences provide developers with guided and intelligent assistance for their development processes in: MongoDB Compass: Where developers can use natural language to compose everything from simple queries to sophisticated, multi-stage aggregations. MongoDB Relational Migrator: Where developers can convert SQL queries to MongoDB Query API syntax. MongoDB Atlas Charts: Where developers can use natural language to generate basic data visualizations. MongoDB Documentation: Where developers can ask questions to an intelligent chatbot, built on top of MongoDB Atlas and Atlas Vector Search, to enable lightning-fast information discovery and troubleshooting during software development. Developer time is one of the most precious commodities in any organization, and with business and customer expectations continuing to rise, developers are under increasing pressure to deliver applications quickly. With more intelligent experiences across the MongoDB developer data platform, it is now simpler and easier than ever to build modern applications for virtually any use case. Check out our AI resource page to learn more about building AI-powered apps with MongoDB. Natural Language Queries in Compass Building queries and aggregations is one of the most prominent developer use cases for Compass , MongoDB’s popular, downloadable GUI tool. Compass’ new, intelligent experience allows developers to use natural language to compose sophisticated aggregations to query, transform, and enrich data, reducing the complexity and learning curve to build queries into application code. The new experience is being released in Public Preview in version 1.40.0 and will be rolled out incrementally to users starting today until the end of October. To get started, make sure you have 1.40.0 downloaded on your machine and have access to the feature. Then you can navigate to the Documents tab and click on the Generate Query button in the query bar, which opens a second bar below the standard query bar where you can enter natural language prompts to generate the Query API syntax for you to execute against your data. Be sure to hit the “thumb’s up” or “thumb’s down” button to rate the helpfulness of the query generated. SQL Query Conversion in Relational Migrator Migrations are part of many developers’ journeys with MongoDB. Earlier this summer at MongoDB.Local NYC, we announced Relational Migrator to help teams with these projects, and we’re continuing to make it easier to modernize application code. Many legacy systems have hundreds, if not thousands of SQL queries that must be modernized as part of any migration effort, and that can be a time-consuming, if not daunting task. Now in Private Preview, developers can use Relational Migrator to convert existing SQL queries and stored procedures into development-ready MongoDB Query API syntax. With SQL query conversion, developers can leverage Relational Migrator to eliminate the manual effort of creating MongoDB queries at scale - speeding up migration projects. SQL query conversion is currently available in Private Preview, and access can be requested directly from the latest version of Relational Migrator. Natural Language Support in Atlas Charts Atlas Charts is the best way for developers to visualize Atlas data. By offering an effortless and powerful solution for gaining data-driven insights, Charts empowers developers and the businesses they help scale. What has always been easy is now becoming more intelligent too! Available in Private Preview, a new natural language mode allows developers to visualize their data through a simple language query, for example: “show me a comparison of annual revenue by country and product.” This is just the start. Later this year, natural language support will extend to more complex queries and chart types. Sign up today to try out natural language support for building charts! Stay tuned for more updates from the team and check out our documentation to learn more about what’s supported by natural language during Private Preview! Intelligent Chatbot for MongoDB Documentation Documentation is critical to the developer experience, making it easier to discover product features and capabilities and troubleshoot common challenges during software development. MongoDB is now super-charging your experience with an intelligent chatbot that improves information discovery by surfacing and summarizing the most relevant documentation. Built with MongoDB Atlas and Atlas Vector Search, the chatbot allows you to ask questions in natural language like “How do I get started with MongoDB Atlas?” or “How do I add a new IP address to the IP access list for my Atlas project?” and receive a response with reference articles, code examples, and other relevant information. MongoDB will also be open-sourcing and providing educational materials about how we built the intelligent chatbot, making it that much easier for others in the community to use the power of MongoDB Atlas and Atlas Vector Search to create dynamic and educational experiences for their end users. Data Privacy and Security MongoDB is trusted by some of the world's most security-conscious organizations, who use the developer data platform’s robust data security and privacy controls to manage their most sensitive data assets. To maintain this trust, these new developer experiences will always be transparent about what data is accessed and used, allowing customers to make informed decisions within the boundaries of their unique security, privacy, and compliance concerns. Get Started Today With new, intelligent features that allow developers to interact with their data using natural language in Compass, Relational Migrator, and Charts, as well as an intelligent chatbot for MongoDB Documentation, it’s easier than ever to take advantage of the flexibility and scalability of MongoDB's document data model to build any class of application. If you have feedback on these experiences, you can enter a suggestion in our user feedback portal .

September 26, 2023

What's New in Atlas Charts: Summer 2023 Release Roundup

Today, we’re excited to announce a series of updates to Atlas Charts . The Charts team is constantly adding enhancements to make visualizing data from MongoDB Atlas collections quick, easy, and powerful. With this summer’s release, we are introducing: Expanded chart customization options in the Charts Embedding SDK An out-of-the-box billing dashboard for easily monitoring your Atlas billing data Support for a new chart type with candlestick charts, and Query execution improvements for more reliable visualization of even your largest datasets. Let’s go through these updates one by one. Expanded charts customization options in the Charts embedding SDK Embedded charts and dashboards can be a useful way to share information across an organization and even with your customers. Over the last year, we have made many improvements to getting started with and implementing embedded charts and dashboards. With this release, we focused on the look and feel of your embedded charts. The Charts Embedding SDK now allows for greater customization across attributes like chart titles, descriptions, axes options, channel options, chart color palette, and conditional formatting options. Providing access to these chart specifications matches many of the customization options that developers rely on when building charts inside Atlas. An out-of-the-box Atlas billing dashboard Next, let’s talk about discovering insights from your Atlas billing data. Over the past two years, MongoDB has made visualizing billing data in Atlas Charts possible . Implementing this dashboard required quite a bit of effort in the past, but we heard from many teams that this dashboard is essential to the monitoring of their Atlas bill. So, we worked to build a more streamlined process for enabling these insights. Enter the new billing dashboard. The new billing dashboard in Atlas Charts is as simple as a button click on our new Ingestions page. Simply click Add and open and you’ll see a billing dashboard ready for exploration. The new billing dashboard allows for customization, adding dashboard filters, and getting new views into your data with the ability to add other charts based on your interests. Support for a new chart type: Candlestick charts The third update in this release is support for candlestick charts. While many developers leverage the wide variety of chart types available in Charts, we are always paying attention to additional chart types that can enable even more use cases for visualizing your Atlas data. This is why we have added candlestick charts with this latest release. Candlestick charts are commonly used for financial data, richly representing financial trading trends and price fluctuations. Query execution improvements for more reliable visualization of even your largest datasets Finally, let’s talk about query execution in Charts. One of the key characteristics of Charts is that it works natively with your Atlas data, requiring no data movement or duplication. Developers can simply select a data source to explore and immediately discover insights about application data. However, that doesn’t mean things are simple on the backend when creating a chart. Charts does a lot of work to efficiently render your visualizations as seamlessly as possible. And depending on your cluster configuration and the complexity of the chart you are creating (and the query driving it), Charts can take some time to render and produce the information you are aiming to visualize. Historically, Charts had a timeout duration of 120 seconds. Queries taking longer than this, would fail and not render the desired visualization. With this update, Charts users will see: Improved rendering of more complex queries as we have extended the timeout duration to 10 minutes, and More helpful in-product notification that lets you know when a query may take additional time to run, so you can continue either creating other visualizations or doing other work, until your query finishes. If you have queries requiring a longer timeout duration than 10 minutes, you can contact the Charts team through support. Note: Query Execution will initially be available through contacting Customer Support, or your existing Customer Success team, to opt-in. The feature will become Generally Available to all accounts in October, 2023. With that, we hope these enhancements make Charts even easier and more powerful to use. Over the coming weeks, we’ll go a level deeper, diving into some of these features with more detail. In the meantime, go build some visualizations in Charts to get hands-on and see for yourself! 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.

August 21, 2023

Exploring Chart Types in MongoDB Atlas Charts

As you begin your chart building journey, you’ll find there are many ways for you to visualize your data in Atlas Charts . Specific data visualization needs vary by team, and we have a growing collection of chart types with various and specific purposes to help you discover insights and communicate effectively. Charts are an essential story-telling piece when working with large amounts of data. Another great way to think of it is that visualizations help condense vast data into a coherent format that makes information more consumable to a wide range of data consumers. When analyzing your data, it's important to recognize that different chart types serve distinct purposes. That is why it's important to choose the right chart type for each potential insight, so that when you put it all together, you have a diverse and all encompassing dashboard. How to effectively use Charts Charts was designed with a simple user interface that makes it quick for you to build charts and visualize your data. However, to properly utilize Charts, this guide on chart types can give you extra help on making charts more quickly and efficiently. Our chart types are split into the following series: Column and Bar Charts Line and Area Charts Combo Charts Grid Charts Circular Charts Text Charts, and Geospatial Charts Determining the best chart type can be an overwhelming task when there are so many to pick from, but knowing the specific strengths of each chart type can help you select the right chart for your use case. Most common chart types in Atlas Charts 1. Data tables What is a data table? Data tables are used to organize data in a tabular view, ultimately allowing viewers to quickly read the results of detailed data. What is an example use case for a data table? A data table can be used for healthcare system applications, where users can store patient information and records, medical history and treatment plans, and enable healthcare professionals to access patient data more easily and effectively. 2. Number charts What is a number chart? Number charts display a single aggregated value from a data field, often representing a grand total or overall state of data. What is an example use case for number charts? A number chart can be used for social media analytics, where engagement metrics, subscriber count, and post performance is summarized for users to track account growth. 3. Grouped column and bar charts What is a grouped column and bar chart? Grouped column and bar charts are used to show detailed data distribution across categories instead of a singular category. What is an example use case for grouped column and bar charts? To analyze financial performance, a grouped column and bar chart would be useful for viewing revenue, expenses, and profits of multiple business units over a period of time. 4. Donut charts What is a donut chart? Donut charts display the proportional distribution of a dataset, often used to showcase the general trends of data instead of exact data values. What is an example use case for donut charts? To track website traffic or customer churn rates, a donut chart is useful to visualize the proportion of website visitors coming from various sources and the percentage of those visitors who have churned or stayed with the company over a period of time. These are a few of the most commonly used chart types in Charts. Now let’s walk through some less common chart types to enrich your data visualization toolkit. Chart types you might have not used in Charts before 1. Line and area charts What is a line and area chart? Line and area charts display a series of data points connected by straight line segments. For area charts specifically, the space beneath the segments are filled with color.. Both of these chart types are used to track trends over time, such as sales and stock prices, or website traffic. What is an example use case for line and area charts? A line and area chart can be used for e-commerce applications, to show sales performance, revenue growth, and profitability trends over specific time intervals. 2. Stacked column charts What is a stacked column chart? Stacked column charts are used to show the composition and comparison of multiple variables over a period of time. They visually look like a series of columns stacked on top of one another, and most useful for analyzing changes across several categories. What is an example use case for stacked column charts? A stacked column chart can be used for product comparison, where the features, prices, and user ratings of various products or services are compared to one another side by side. 3. Geospatial charts What is a geospatial chart? Geospatial charts are map-based charts that are created from geospatial data and other forms of data to define specific geographical locations in the form of latitude and longitude coordinates or text fields with country and state names. Atlas Charts allows users to visualize geospatial data in three different chart formats: choropleth, scatter, and heatmap. What is an example use case for geospatial charts? A geospatial chart can be used for environmental monitoring, where soil and air quality data, pollution levels, deforestation rates, and other environmental factors are analyzed to locate areas for conservation. 4. Heatmaps What is a heatmap? Heatmaps are used to show relationships between two variables, showcased in a tabular format as a range of colors. Darker, more intense shades represent larger aggregated values while lighter shades represent smaller aggregated values across the dataset. What is an example use case for heatmap charts? A heatmap chart can be used for user behavior analytics, where user interactions, clicks, and total engagement across different web pages are tracked and monitored to improve customer experience. Now you have an idea of the many chart types, common and uncommon, that are available to you in Atlas Charts. Now it’s time to give it a try! Use your own data, or some of MongoDB’s sample datasets, to practice what you’ve learned and implement your next charting option! Log in to Atlas Charts today to create your visualizations! New to Atlas Charts? Get started today by logging into or signing up for MongoDB Atlas .

August 2, 2023

What's New in Atlas Charts: Suggested Charts, Auto Activation, and Contextual Help

Atlas Charts is the native data visualization tool for quickly and easily analyzing your data in MongoDB Atlas. Today, we’re announcing a collection of updates that further streamline the Charts experience: Suggested charts: a quicker way to build visualizations More contextual help in the chart builder Automatic Charts activation for all project members Suggested charts Charts has always offered a simple UI with an easy to use, drag and drop interface that lets you quickly build charts and visualize your application data. However, we still found that some users could benefit from extra help when building out new charts. Rather than starting from an empty screen where you need to drag appropriate fields into the chart type selected, what if you could simply select an automatically suggested chart, and start applying customization from there? That’s exactly what suggested charts offer. We experimented with this feature late last year and now we have turned it on for everyone! Simply add a chart into one of your dashboards to try it out today. Figure 1: Using the new auto suggested charts in the chart builder. Help button in the chart builder As you might expect, the chart builder is where you do your chart creation. Similar to suggested, last year we experimented with ways to provide more contextual help for users when building new charts. Now, we are surfacing helpful docs articles to educate users on key chart building topics like: filtering, adding fields, selecting the right chart type, and more. Sometimes it can be intimidating to know exactly what chart to use and how to achieve the style and customization you want – the help button in chart builder will make this much easier. Building a chart and have a question? Just click into the Get help button and check out one of our highlighted topics, or choose View all topics to read the main Charts documentation. Streamlining Charts activation We’re constantly looking for ways to help Atlas users with data visualization quicker. So starting with this latest release, when you click into the Charts tab from the Atlas UI, you will automatically be set up to start visualizing your data – no activation required. Additionally, Atlas users browsing collections within a specific cluster, can now more quickly navigate directly into Charts for quick visualization. When viewing a collection, the Visualize your data button, seamlessly opens in the chart builder with the current collection selected as the chart’s data source. Paired with the new suggested chart, users see a list of chart suggestions to quickly and easily build a relevant chart based on their collection data. Note: you may see a “Charts” tab in the collection view instead of the Visualize your data button, as shown below. This is due to an experiment we are currently running. FIgure 3: Seamlessly navigate from an Atlas collection into the chart builder in Atlas Charts. This is a continuation of our effort to optimize the overall Charts experience. Last year we made strides in this area by introducing features like streamlined data sources and org-wide sharing . Keep on the lookout for more Charts features that further simplify your experience visualizing Atlas data across your team. 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.

May 4, 2023

What's New in Atlas Charts: Schedule Dashboard Reports to Share Data with Your Team

Today, we’re introducing an exciting feature addition for teams using Atlas Charts . Charts project owners can now schedule dashboard reports to be sent via email to keep team members informed about key data. This feature has been heavily requested by some of our largest users as there are many use cases where dashboards may be valuable to your team, but you don’t necessarily want to require anyone to do extra work to access and view data. Enter scheduled dashboard reports in Atlas Charts! In any dashboard that your team relies on for regular data review, simply schedule a dashboard report. The new Schedule button can be found at the top right of the dashboard screen: Once you’ve chosen a dashboard from which to create a report, you will see a variety of options letting you customize the content and frequency of your report before you schedule. A report requires basic fields like a name or subject line, recipient list, and optionally, a message for the body of the email. In addition to a link to the dashboard in Charts, you can choose whether to attach an image or PDF for quick reference in the message itself. Finally, you can set a schedule of daily, weekly, monthly, or quarterly delivery. You can also simply send a single email if you have a one-time need to share a report. And once you’ve set everything up, your email will be sent on your defined schedule. As you use scheduled dashboard reports more and more, we created a Reports page where you can manage all reports in your project. Note that if you’re on an free tier, you can try one scheduled report. If you’re on an M2 cluster or higher, you can create up to 100 reports per project. To learn more, please check out our documentation . We’re always listening to feature requests that will enhance using Charts across teams, so if you have any requests or feedback, please share them with us here . Log in to Atlas Charts today to schedule your first report! If you’re new to Atlas Charts, get started today by logging into or signing up for MongoDB Atlas.

April 13, 2023

Visualizing Your MongoDB Atlas Data with Atlas Charts

MongoDB Atlas is the leading multi-cloud developer data platform. We see some of the world’s largest companies in manufacturing , healthcare , telecommunications , and financial services all build their businesses with Atlas at their foundation. Every company comes to MongoDB with a need to safely store operational data. But all companies also have a need to analyze data to gain insights into their business and data visualization is core to establishing that real-time business visibility. Data visualization enables the insights required to take action, whether that’s on key sales data, production and operations data, or product usage to improve your applications. The best way to do this as an Atlas user is by using Atlas Charts – MongoDB’s first-class data visualization tool, built natively into MongoDB Atlas. Why choose Charts First, Charts is natively built for the document model. If you’re familiar with MongoDB, you should be familiar with documents. The document model is a data model made for the way developers think. And with Charts, you can take your data from documents and collections in Atlas, and visualize them with no ETL, data movement or duplication. This speeds up your ability to discover insights. Second, Charts supports all cluster configurations you can create in Atlas, including dedicated clusters, serverless instances, data stored in Online Archive, as well as federated data in Atlas Data Federation. Typically when you learn about a company’s integrated products and services, you find some “gotchas” or limitations that make any benefits come at a significant cost. In the case of a MongoDB Atlas customer, that could come in the form of someone finding out that a cluster configuration option isn’t supported by Charts. But that will never be the case. If you create and manage your application data in Atlas, you can visualize it in Charts. That’s it. Third, Charts is a robust data visualization tool with a variety of chart types, extensive customization options, and interactivity. Compared to other options in the business intelligence market, you get the same key benefits, without all the complexity. You can learn how to use Charts in a few hours and you can easily teach your team. It’s the simplest data visualization solution for most teams. Fourth, the value of Charts can extend beyond individual use cases, with sharing and embedding . This lets you both flexibly share charts and dashboards with your team, as well as embed them into contexts that matter most to your data consumers, such as in a blog post or inside your company’s wiki. Finally, Charts is free for Atlas users up to 1GB per project per month, which covers moderate usage for most teams. There are no seat-based licensing fees associated with Charts, so no matter how many team members you have, Charts will remain a low-cost, if not zero cost solution for your data visualization needs. Beyond the included free usage, it’s just $1/GB transferred per month. You can check out more pricing details here . How to use Charts The best way to learn how to use Charts is to simply give it a try. It’s free to use and we have a variety of sample dashboards you can use to get started. But let’s walk through some basics to help illustrate the kinds of visualizations that Charts can enable. Charts makes visualizing your data easy by automatically making your Atlas deployments (any cluster configuration) available for visualization. If you’re a project owner, you can manage permissions to data sources in Charts. We could write an entire blog post on data sources, but if you’re just getting started, just know that your data is made easily available in Charts unless your project owner intentionally hides it. Create a dashboard Everything in Charts starts with a dashboard and creating a dashboard is easy. Simply select the Add Dashboard button at the top right of the Charts page in Atlas . From there, you’ll fill in some basic information like a title and optional description, and you’re on your way. Here’s what one of our new sample dashboards looks like. They are a great place to start: Build a chart Once you have a dashboard created, you can add your first chart. The chart builder gives you a simple and powerful drag and drop interface to help you quickly construct charts. The first step is selecting your data source: Once you have a data source selected, simply add desired fields into your chart and start customizing. The example below uses our IoT sample dashboard dataset to create a bar chart displaying the total distance traveled by different users. From there you can add filters and further customize your chart by adding custom colors, data labels, and more. The chart builder even allows you to write, save, and share queries and aggregation pipelines as shown below. You can learn more in our documentation. Play around with the chart builder to get familiar with all of its functionality. Share and embed A chart can be useful in itself to individual users, but we see users get the most benefit out of Charts when sharing visualizations with others. Once you have created a dashboard with one or more charts, we offer a variety of options letting you share your dashboards with your team, your organization, or via a public link if your data is not sensitive. If you would rather embed a chart or dashboard where your team is already consuming information, check out Charts embedding functionality. Charts lets you embed a chart or dashboard via iframe or SDK, depending on your use case. Check out our embedding documentation to learn more. That was just a brief overview of how to build your first charts and dashboards in Atlas Charts, but there’s a lot more functionality to explore. For a full walkthrough, watch our product demo here: Atlas Charts is the only native data visualization tool built for the document model and it’s the quickest and easiest way to get started visualizing data from Atlas. We hope this introduction helps you get started using Charts to gain greater visibility into your application data, helping you to make better decisions on your data. Get started with Atlas Charts today by logging into or signing up for MongoDB Atlas , deploying or selecting a cluster, and navigating to the Charts tab to activate for free.

March 16, 2023

What’s New in Atlas Charts: New Sample Dashboards and Embedding SDK Improvements

Atlas Charts is the best data visualization tool for quickly and easily analyzing all your Atlas data. Today, we’re announcing two big updates: New sample dashboards to give you even more inspiration when getting started Charts Embedding SDK enhancements: dashboard filters and save as PNG Let's start with sample dashboards We took a look at the current experience for new Charts users building their first dashboards. To help reduce the time it takes to experience the power of dashboards, we have always offered a sample dashboard that used a movie database to help explore Charts basics like chart types and understanding how a data source and fields work. While any dataset can be interesting and most of us enjoy watching movies, we knew that most development teams could benefit from some tangible examples of how they might visualize their application data in Charts. So we thought about a few key use cases that nearly every team must consider and we put together four new sample dashboards analyzing: product usage, sales or general business metrics, IoT sensor data, and finally, observability or log data commonly used to understand a platform’s reliability. All of these new dashboards are now available to every Charts user, and each provides a great starting point for exploring your data in Charts. Choosing the new sample IoT dashboard in Atlas Charts. With these new sample dashboards as inspiration, you will be able to quickly see the potential of complex dashboards and customize them to fit your own data and gain valuable business insights. Embedding SDK enhancements: Dashboard filters and save as PNG Next, we are continually listening to customers and trying to make our Embedding SDK more useful for diverse use cases. If you’re unfamiliar, the Embedding SDK lets you take charts and dashboards from Charts, and embed them into the contexts that matter most to your users, with rich customization. Up to this point, dashboard filters have only functioned in dashboards built within the Charts UI in MongoDB Atlas. Dashboard filters can be used to dig a level deeper into your datasets, and with interactive filtering , they are the foundation from which you can add interactivity into embedded dashboards. With this update, users can now seamlessly filter data directly within the embedded dashboard , providing a more interactive experience and enhancing data exploration. Setting up dashboard filters in the UI is simple, and once they’re enabled, you can either selectively choose the fields allowed for filtering or allow all fields present in the data sources used in the dashboard. You can also allow all fields present in a data source if you use chart embedding. Configuring an embedded dashboard with dashboard filters in the IoT sample dashboard. Taking the field ‘calories’ as an example used in the video above, in the SDK, you can easily set a dashboard filter to plot a chart with users who have spent more than 1000 calories: dashboard.setFilter({ calories: { $gt: 1000 } }); You can also use the getFilter method to see what filters have been applied to the embedded dashboard: dashboard.getFilter(); Additionally, you can now programmatically save an image of any chart as a PNG, in either base64 or binary formats using the getImage method in the SDK. We are excited to see how you use the sample dashboards and dashboard filtering in embedded dashboards to achieve your visualization goals using Atlas Charts. 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.

February 27, 2023

What’s New in Atlas Charts: Easy Organization-Wide Sharing

We’re excited to announce improvements to sharing dashboards in MongoDB Atlas Charts . Data visualization is a powerful tool for discovering insights, and sharing visualizations across your team helps amplify those insights to propel businesses forward. With organization-wide sharing in Atlas Charts, we’re making it even easier to share the insights you discover from your application data across your entire organization. Sharing dashboards Atlas Charts has always made it possible to share visualizations with either individual members or everyone inside your Atlas project. Assuming a user had access to a given data source in Atlas, adding a user to a Charts project was effectively a one-click process. However, many teams do not broadly share database access unless an individual specifically needs it. And, if you want to share data with many members of your team, provisioning users one by one is tedious. Once users are in a Charts project, however, sharing a dashboard with everyone inside the project becomes relatively easy — you can invite all users in your project to view your dashboard with a single action. There are probably scenarios in which some members of your organization have Atlas access and others do not. In this case, if your team has enabled Federated Authentication and uses a third-party authentication provider, such as Google or Okta, Charts now makes it simple to turn on sharing dashboards across your entire organization. Granting access This approach makes sharing company-wide information quick and easy. For example, you can keep employees aware of product or platform growth or other key business metrics. Any members of your organization can be granted access to view these dashboards with a single click, as shown in Figure 1. Figure 1: &nbsp; A look at a dashboard shared across an organization. Note that, with these changes to dashboard sharing, your ability to maintain the security of your data remains unchanged. New dashboard viewers still need at least viewer access to any data source behind the charts in a shared dashboard, thereby ensuring that your company's sensitive data remains private. Additionally, project owners can now manage data source access at a deployment level, which means they can give access to their clusters or federated database instances . This capability is in addition to the already available granular control of data source access at a collection level, which was introduced as part of recent improvements we made to data sources. You can read more about managing access to data sources in your organization in our documentation . We hope you find these sharing improvements valuable and start leveraging this capability to share additional insights across your organization. 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.

December 5, 2022

Atlas Charts Adds Support for Serverless and Online Archive Data Sources

We recently introduced streamlined data sources in Atlas Charts, which eliminates the manual steps involved with adding data sources into Charts. With MongoDB Atlas project data automatically available in Charts, your visualization workflow can become quicker and simpler than ever. With this feature, Atlas Charts users can now visualize two new sources of data: Serverless instances and Atlas cluster data that’s been archived using MongoDB Atlas Online Archive . For those unfamiliar with these data sources, here’s a quick summary: A serverless instance is an Atlas deployment model that lets you seamlessly scale usage based on workload demand and ensures you are only charged for resources you need. Online Archive enables automated data tiering of Atlas data, helping you scale your storage and optimize costs while keeping data accessible. Use cases These data sources serve two distinct use cases, based on your needs. So, whether you are trying to eliminate upfront resource provisioning using a serverless instance or creating archives of your high-volume workloads, such as time-series or log data to reduce costs with Online Archive, Charts makes these sources natively available for visualization with zero ETL, just as it always has with your other Atlas clusters. To learn how easy it is to visualize these new data sources, let’s create a serverless database called “ServerlessInstance0” and separately activate Online Archive on a database called “Cluster0” that will run daily in Atlas (Figure 1). Figure 1: Screenshot showing a serverless database deployed in MongDB Atlas. When setting up an Online Archive, Atlas creates two instances of your data (Figure 2). One instance includes only your archived data. The second instance contains your archive data and your live cluster data. This setup gives you additional flexibility to query data as your use case demands. Figure 2: Screenshot showing Online Archive instances in Atlas. Moving on to the Data Sources page in Charts (Figure 3), all of the data sources are shown, including serverless instances and Atlas cluster data archived in Online Archive, neatly categorized based on the instance type and ready for use in charts and dashboards. (Note that project owners maintain full control of these data sources.) For more details about connecting and disconnecting data sources, review our documentation . Figure 3: Screenshot showing Serverless and Online Archive data sources in Atlas Charts. With these additions, Charts now supports all the cluster configurations you can create in Atlas, and we are excited to see how you achieve your visualization goals using these new data sources. 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.

October 27, 2022