Introduction

Deploying on cloud platforms can be difficult: When you work with AWS, Azure, or GCP, doing everything by hand can introduce mistakes and cause delays. But with Terraform, you can automate setups for all kinds of applications, including Bold BI^®. This makes the setup process faster, more reliable, and easier to manage. First, let’s explore why using Terraform for Bold BI deployment is a great approach.

Why use Terraform for Bold BI deployment?

Terraform is a tool that automates the setup and management of cloud services by using code, ensuring consistent and repeatable infrastructure. When deploying Bold BI across cloud providers and services, offers a powerful way to manage infrastructure with efficiency, consistency, and control.

• Repeatable setups: Instead of tediously configuring Bold BI manually, the same script can be used to deploy it in various environments, such as testing or production, without forgetting any key settings.
• Easy scaling: Terraform lets you ramp up resources quickly to accommodate big data or a growing user base while ensuring minimal performance interruption.
• Teamwork: Since Terraform scripts can be stored with version control systems such as Git, your team can easily collaborate on updates and modifications, resulting in increased team.
• Smart cloud spending: Terraform allows you to keep track of deployed resources to prevent waste and keep your deployments cost-effective.
• Seamless updates: Terraform is used within DevOps environments, allowing for regular updates or modifications to your Bold BI environment with less downtime and manual effort.

Deploy Bold BI on AWS ECS with Terraform

Terraform simplifies deploying Bold BI on Amazon Web Services’ Elastic Container Service (ECS). It handles the creation of resources such as load balancing and container management, speeding up the deployment process and improving performance while ensuring enhanced scalability.

To deploy Bold BI on AWS ECS, follow the steps in this documentation.

Deploy Bold BI on AWS EKS with Terraform

For Kubernetes-based deployment, Terraform handles the setup of AWS Elastic Kubernetes Service (EKS), configuring EKS clusters, node groups, and network resources such as VPCs, subnets, and security groups. This results in faster deployment times and ensures your environment is high performing.

You can deploy Bold BI on AWS EKS by following the steps provided in this documentation.

Deploy Bold BI on AKS with Terraform

Deploying Bold BI on Azure Kubernetes Service (AKS) with Terraform simplifies the configuration of AKS clusters, node pools, and network components. It accelerates the setup process and ensures your environment is secure and highly available.

To deploy Bold BI on AKS using Terraform, follow the steps provided in this documentation.

Deploy Bold BI on GKE with Terraform

Deploying Bold BI on Google Kubernetes Engine (GKE) by using Terraform handles the creation of GKE clusters, node pools, and network resources like VPCs and firewall rules. This ensures that deployments are repeatable and maintain a high level of availability for your BI workload.

Follow the steps in this documentation to learn how to deploy Bold BI on GKE by using Terraform.

Conclusion

Automating your Bold BI setup with Terraform makes cloud deployment easier and more reliable across AWS, Azure, and GCP. With the setup process simplified across platforms, you’re now ready to move forward with confidence. Take control of your cloud infrastructure and business intelligence environment—try Bold BI^® for free and start using Terraform today.

Introduction

Creating visuals quickly is now easier than ever with Bold BI’s AI assistant in embedded analytics. It helps users turn complex data into simple, engaging visuals. This guide will show you how to activate the AI assistant in your embedded application, unlocking powerful, AI-driven insights. Enhance the user experience and streamline decision-making by bringing automated data analysis right into your app.

Understanding Bold BI’s AI assistant

Bold BI’s AI assistant is an advanced tool designed to enhance your embedded analytics experience in both the dashboard designer and viewer mode. It leverages artificial intelligence capabilities like NLPS to streamline data interaction, providing users with fast results. Activating an AI assistant in embedded analytics apps empowers users with faster insights, personalized recommendations, and an enhanced user experience.

Activating the AI assistant in embedded platforms

First, ensure that the AI assistant is enabled in your Bold BI^® tenant settings to make it accessible within your app. This initial setup is essential to allow users to interact with and activate the assistant effectively. To do this, please follow the steps provided in this documentation.

Once the AI assistant is enabled, you can activate it in your embedded application.

Activating the AI assistant on cloud environments

To activate the AI assistant in your cloud environment, follow these steps:

Step 1: To begin, locate the AI Assistant icon positioned at the bottom-right corner of your dashboard, either in designer or viewer mode. Clicking this icon will initiate the activation process.

Upon clicking the icon, the AI Assistant activation dialog will be displayed. This page contains essential information about the feature and the activation process.

Step 2: It’s important to understand how your data will be processed by the AI Assistant. Review the AI data processing procedure carefully. Once you acknowledge this information, the Activate now button will become enabled. Click it to proceed with the activation.

Step 3: Once the activation process is complete, you need to click Continue.

After this, you will be directed to a page confirming that the AI assistant has been activated, as shown.

Activating the AI assistant on-premises

For our on-premises users, additional steps are required to ensure the AI assistant is updated correctly within your embedded platform. After completing steps 1 to 3 in the previous instructions:

1. Click Manage License to navigate to the license management page. Here, update the license with AI assistance enabled in the on-premises environment.

   

2. Click the Refresh License tab to include the updated license key that enables the AI assistant feature in your environment.

   

Let’s see how users can activate the AI assistant in both online and offline environments.

Activating the AI assistant online

For the on-premises users using the online version, sign in with your account credentials to activate the AI assistant after following the previous steps.

Activating the AI assistant offline

For on-premises users who want to activate the AI assistant offline, please refer to this KB article, which outlines the necessary steps.

Once the activation process is complete, you need to click Continue. You will be directed to a page confirming that the AI assistant has been activated, as shown in the following screenshot. Click Get started to begin utilizing your new AI assistant feature.

Once the AI assistant is activated, you can embed dashboards into your application anywhere and use it to interact with your data more efficiency. This AI assistant will be displayed at the bottom-right of your dashboard, as shown.

Once the AI assistant is activated, you can easily access metrics, streamline data analysis, and enhance decision-making within the embedded analytics platform. Get started today and unlock the potential of AI-driven analytics with this powerful feature! For more information, please visit our documentation.

Conclusion

In today’s quick-moving business world, using smart tools like Bold BI’s AI assistant can greatly enhance decision-making and efficiency. By embedding AI-powered analytics in your business, you and your team can glean insights more quickly, leading to data-driven strategies.

Get started with Bold BI^® today by signing up for a free trial. For a closer look at the capabilities of our AI assistant and how Bold BI uses natural language processing, visit our webinar and check out our webinar show notes blog for a comprehensive summary and key takeaways. Learn more about its key embedded analytics features, like the AI assistant, to enhance your dashboard creation and data visualization capabilities. For any inquiries, please feel free to contact our support team via the Bold BI website. But if you already have an account, please log in to submit your questions.

Managing and analyzing large datasets, like those containing billions of records, can be a daunting task. Bold Data Hub is specifically designed to simplify this process, making it easier to handle vast datasets without compromising dashboard performance. Let’s explore how Bold Data Hub empowers you with seamless migration and optimization for large datasets.

What is Bold Data Hub?

Bold Data Hub provides powerful extract, transform, and load (ETL) capabilities, allowing you to integrate multiple sources into a single, efficient pipeline for your data warehouse. It simplifies the process of extracting, processing, cleaning, and transforming data from various sources into PostgreSQL, Microsoft SQL Server, MySQL, Oracle, Google BigQuery, Snowflake, Apache Doris, and Bold BI^® data stores.

The challenge of managing billion-row datasets

Managing large datasets can be complex, primarily due to three key challenges:

1. Data size and complexity: Large datasets often come from multiple sources, each with different structures, making it difficult to consolidate and process the data effectively.
2. Performance bottlenecks: Without proper optimization, dashboards handling vast amounts of data can become slow or unresponsive.
3. Schema variability: Inconsistent column names and data types make maintaining data integrity a challenge during migration.

These challenges require a sophisticated solution to ensure smooth data management and performance. So, let’s explore how Bold Data Hub addresses these challenges through structured migration and optimization strategies.

Bold Data Hub streamlines data migration and optimization

Bold Data Hub offers robust ETL capabilities to simplify data management for large datasets. The migration process with Bold Data Hub follows these steps:

1. Data splitting: The immense dataset is divided into two large CSV files to facilitate batch processing and manage loading complexity.
2. Schema harmonization: Using Bold Data Hub’s transformation capabilities, column names and data types are synchronized to ensure consistency across datasets.
3. Loading into databases: The transformed data is loaded into Apache Doris or PostgreSQL to leverage their high-performance query capabilities for big data analytics.

Migrating over 1 billion NYC taxi rides into a data warehouse with Bold Data Hub

To show off the impressive capabilities of the Bold Data Hub, we’ll demonstrate how you can migrate a dataset to a database and optimize its performance.

We take a sample data set of over 1 billion records. For this example, we are using the NYC Yellow Taxi dataset, which is a repository of detailed records of taxi trips within New York City. Key attributes of the dataset include:

• Trip details: Pickup and drop-off timestamps, trip distance, and passenger count.
• Fare components: Base fare, extra charges, taxes, tips, tolls, and total fare.
• Geospatial data: Latitude and longitude of pickup and drop-off locations.
• Operational metrics: Payment type, vendor ID, and rate codes.

You can download the sample datasets we used: nyctripstaxi.csv and nyctripstaxi2.csv.

Steps to migrate data with Bold Data Hub

1. 1. Access the Data Hub site
      On the Bold BI application home page, click Data Hub to access the Bold Data Hub site. The home page will open.

      

   2. Prepare your data for migration
      Before proceeding, large datasets, such as the NYC Yellow Taxi dataset, may need to be divided into smaller CSV files for efficient loading and batch processing. This step reduces complexity and enhances migration speed.
   3. Create a new migration project
      • On the Bold Data Hub site, select Add Pipeline, upload the CSV files, and begin the data migration process.
      • Select Apache Doris or PostgreSQL as your target database in the Bold Data Hub interface.
      • Load the CSV files through a configuration template and then save the project. Once saved, you can schedule ETL jobs on demand or at custom intervals.

4. Handle schema changes
   Use Bold Data Hub’s transformation tools to ensure that column names and data types remain consistent across your files. This step is crucial to prevent any errors during migration.

For a detailed explanation of how to create a Bold Data Hub project to transform and load data into your desired database, follow the steps listed in “Working with Bold Data Hub” in the Bold BI documentation.

After creating the project for the NYC Yellow Taxi dataset, it will be generated as a data source within the Bold BI platform. We can now create a dashboard that visualizes this data.

Creating a dashboard from the Bold Data Hub data source

Using Bold BI’s intuitive dashboard designer, we built the NYC Yellow Taxi Trips dashboard to provide in-depth analysis of the taxi trip dataset that is composed of over 1 billion rows. In this dashboard, users can explore essential financial metrics, including total fare amounts, MTA tax collected, and tip amounts, to gain valuable insight into taxi operations.

Let’s now look at a powerful optimization technique implemented in Bold Data Hub that boosts performance further:

Performance optimization with materialized views

Materialized views are precomputed tables that store aggregated results. These views significantly reduce query times by enabling rapid data retrieval, especially when handling repetitive queries. By using materialized views, Bold Data Hub ensures your dashboards render faster and more efficiently.

Refer to these articles for more information about implementing materialized views in Bold Data Hub:

• Materialized Views in Apache Doris
• Materialized Views in PostgreSQL

Finally, let’s compare dashboard performance metrics between the Apache Doris and PostgreSQL data warehouses.

Performance metrics for migrating billions of rows of data into a data warehouse

To illustrate the effectiveness of Bold Data Hub, we can examine performance metrics when migrating large datasets. The following table lists the metrics observed while migrating the 1 billion & 10 billion dataset to an Apache Doris data warehouse:

Optimized dashboard performance metrics

We compared query performance for the NYC Yellow Taxi dataset on Apache Doris and PostgreSQL with and without materialized views. The migration was executed on a machine with the following configuration for both databases: 128 GB of RAM, 32 CPU cores, and 500 GB of storage.

Key insights

Apache Doris:

• Without materialized views: Rendering took 26 seconds.
• With materialized views: Rendering time reduced dramatically to just 8 seconds.

PostgreSQL:

• Without materialized views: The dashboard failed to render, resulting in a time-out.
• With materialized views: Rendering time improved to 10 seconds, although still slower than Doris with materialized views.

These metrics highlight the critical role of materialized views in optimizing query performance, especially when handling extensive datasets.

Conclusion

Bold Data Hub’s ability to efficiently migrate and optimize large datasets was demonstrated in this blog through its taming of the billion-record NYC Yellow Taxi data collection. Through strategies and techniques like data splitting, schema harmonization, and materialized views, Bold Data Hub ensures that even the largest datasets are managed effectively to deliver insightful dashboards without performance degradation. Begin your Bold BI^® journey with a free trial!

To learn more about how Bold Data Hub can optimize your data management, contact us through the Bold BI website or, if you already have an account, you can log in to submit your questions.

Have you ever wondered how fast you can process and visualize over a billion rows of data? With the right tools, it can be done in just six seconds!

With the Syncfusion^® Big Data Platform, you can process billions of rows of data, and with Bold BI^®, you can visualize that data in under a minute without writing a single line of code.

Why is fast data loading important in dashboards?

Fast data loading is essential for ensuring a seamless user experience and maximizing the effectiveness of dashboards. When users can load more data in dashboards quickly, it leads to numerous benefits, including:

• User experience: Users seek quick access to information. Rapid data processing enhances their ability to engage with and analyze data efficiently.
• Real-time decision-making: Speed allows businesses to analyze data instantly and make quick, informed decisions.
• Enhanced productivity: Efficient data processing and visualization optimize workflows, enabling teams to achieve more in less time and concentrate on strategic initiatives rather than waiting for data.
• Minimized waiting time: Quick data loading and visualizations reduce delays, making it easier for users to access and use their data.

How to load and visualize a billion rows in a dashboard

The Syncfusion Big Data Platform can process billions of data points with impressive response times, and Bold BI can display those data points in stunning dashboards in under a minute. By using these solutions together, you will unlock insights from deep within your data and make business decisions quickly.

Visualizing over 1.1 billion NYC taxi rides with dashboards

To show off the impressive capabilities of the Big Data Visualization Platform and Bold BI, we’ll demonstrate how you can visualize a billion NYC Taxi rides in one dashboard.

We take a sample data set of over 1.1 billion records from the New York City Taxi & Limousine Commission dataset from NYC Open Data. This dataset contains all taxi trips that occurred between 2009 and 2015 in New York City.

After uploading the data to the Big Data Platform, tuning it, caching it, and partitioning it, we then use Bold BI to visualize it.

Now, let’s connect the data through a SparkSQL data source. To create a SparkSQL data source from the Bold BI dashboard designer, follow the steps listed in “Choose the SparkSQL data source” in the Bold BI documentation. After authenticating the database, click Connect to connect to the SparkSQL server that’s been configured. Drag the table from the left pane into the center pane and then save the data source. This can be accomplished in less than 30 seconds.

The created data source will be added to the DATA SOURCES panel. Once the data source is created, add the widget you want to visualize the data with to your dashboard by dragging and dropping it onto the designer surface. In this demonstration, we’ll use a bar chart widget.

Assign data to the added widget. Apply aggregate functions to the columns you’re going to visualize.

Once the data is assigned, you are visualizing billions of rows, simplifying complex information for quick comprehension. In the following figure, we use three separate charts to summarize over a billion records in business dashboard.

Click Preview to view the full dashboard.

Save time and money with Bold BI

You have seen how massive amounts of data can be visualized in just a few seconds by using these Syncfusion platforms. Not only do they save you time, but they also save you money. Check out the Bold BI interactive pricing calculator to see how affordable our enterprise-grade data visualizations are.

If you want to learn more about this topic, visit our YouTube channel or watch the video here.

Bold BI^® empowers businesses to unlock valuable insights from vast and complex datasets. With seamless, hassle-free integration, it connects to diverse data sources, enabling you to make confident, data-driven decisions. Don’t hesitate—start using Bold BI today by signing up for a free trial and discover the future of data visualization!

Introduction

Enriching the presentation of your data is key to conveying information clearly. Rich text is one such tool for this purpose in a dashboard. In this blog, we’ll explore how to use rich text in dashboards to enhance your data presentation, ensuring your dashboards not only inform but also captivate your audience.

What is rich text?

Rich text is text that is modified with style and formatting customizations like bold, underline, and italics. Depending on the software behind it, rich text may also support text colors, different font sizes, hyperlinks, and code blocks.

What is a text widget?

A text widget is an interactive editor that allows you to create and display rich text formatted with tables, hyperlinks, code, and more. Text widgets in dashboards facilitate easy data entry and presentation.

Features of the text widget in Bold BI

Font formatting: You can format text with various font styles, sizes, colors, and alignments, including bold, italic, underline, strikethrough, superscript, and subscript.

Background customization: You can customize the text’s background with images or colors and modify the background’s transparency settings.

Toolbar modes: The Bold BI^® text widget’s toolbar can be displayed inline to reduce the amount of space it occupies or floating to display the entire toolbar.

Hyperlinks and tables: You can create and edit tables and insert hyperlinks while utilizing various customization options in the Bold BI text widget.

HTML editing: The Bold BI text widget lets users edit HTML markup and view the output.

How to configure a text widget in Bold BI

1. In the Dashboard Designer, drag and drop the Text widget from the visualization panel into the design canvas.
2. Click the Pencil button on the widget to access its editing functionality.
3. Type text and use the toolbar to format it, add tables, insert hyperlinks, and more.
4. Customize the widget’s appearance using the Properties panel on the right.
5. Click Preview to view the dashboard and determine whether further changes need to be made to the widget’s content or appearance.

The following GIF shows the configuration process.

Use cases of text widgets in dashboards

Customer service

The Customer Satisfaction Dashboard, shown in the following figure, uses text widgets to provide key takeaways from gauges charting the customer effort score and net promoter score, enabling users to quickly understand these metrics. This helps the customer support team effectively present their performance data in the dashboard.

Construction

The text widget within the Construction Project Monitoring Dashboard  displays , thereby facilitating efficient tracking and management. This functionality provides users with comprehensive project details for any selected category, aiding in meticulous project planning.

Education

The Student Profile Dashboard’s text widget displays students’ personal details, contact information, and select academic data in tables for convenient, quick access. Note that rich-text formatting is used to produce both tables and bold text, and the multitab functionality is built into the text widget.

Government

The text widget in the Crime and Safety Management Dashboard displays data pertaining to crime statistics, such as total population, reported crimes, solved crimes, and the unresolved crisis. This information gives government a high-level overview of crimes and their proportion to their constituent population.

To learn more about these dashboard texts, refer to our Bold BI dashboard examples.

Best practices for using rich text in dashboards

To maximize the impact of rich text in dashboards, consider these best practices:

• Clarity and brevity: Keep your text concise and to the point.
• Formatting: Use formatting options like bold, italics, and bullet points to highlight or emphasize key information. Don’t apply formatting just because you can.
• Consistency: Maintain a consistent style, including font type, size, and color, to ensure a cohesive look.
• Contextual information: Use rich text to provide context or explanations for the data displayed. This helps users understand the significance of the data.
• Placement: Position rich text strategically. Place it near the relevant data visualizations to provide immediate context without cluttering the dashboard.

Conclusion

Rich text in dashboards enriches the user experience by delivering carefully formatted and designed text that enhances data comprehension. Enhance your dashboards’ effectiveness by leveraging rich text and text widgets to present key insights clearly and engagingly. You can add text widgets to dashboards in Bold BI^® by following the configuration process outlined in this blog post. If you’re not a Bold BI user, start with a free trial. For more information, visit our website or contact our support team.

Introduction

Electronic signatures have become an essential part of the current business environment, streamlining processes and enhancing efficiency. BoldSign’s online signature generator enables users to draw and save their signatures as images that can be easily reused. This tool supports efficient digital signatures for online signing and does not require an account, offering open access.

Signature generator

BoldSign’s signature generator allows you to create a digital version of your wet signature on any device—computer, tablet, or mobile phone. Simply access the tool and draw your signature using a mouse, stylus, or finger. Once created, you can save it for future use in any of your documents. This helps maintain a professional appearance by ensuring your signatures are consistent across all documents.

Features of the signature generator

The signature generator offers customization options to help you create your perfect digital signature.

Pick your preferred color

Select a color that aligns with your brand. Available color options include black, blue, green, and red.

Clear, redo and undo signatures

Creating a signature with a cursor or stylus is different from a pen, so it can be prone to error. If you’re not satisfied with your attempt, you can clear it and start over whenever needed. You can also create multiple versions of your signature, use the undo and redo buttons to compare different versions, and save the best one from your attempts.

Download your personalized signature

Once you’ve created your digital signature, download it using the Download as PNG button. After downloading, you can store your signature in any location, making it easy to access and apply it to documents anywhere, at any time.

Add your saved signature to documents

BoldSign^® provides an eSignature app that facilitates creating signature requests, electronically signing documents, and managing the process efficiently. When you start the signing process in the app, you can effortlessly use and apply the signatures you’ve created with the signature generator.

Conclusion

We value the time that you invested in learning how to use our new, free signature generator to make personal electronic signatures. Visit BoldSign^® to experience document signing at its best. Sign up for a free trial to explore BoldSign’s features or a demo to gain further insights into its functionality. For any questions or issues, please contact us through our support portal.

Introduction

Embedding analytics in React JS applications is crucial for real-time insights and user experience. React JS embedding empowers developers to integrate analytics seamlessly, enhancing app functionality and interactivity. To enhance the customer experience and simplify the embedding process in applications, Bold BI^® has added Token API member support in the JS embedding feature starting from version 7.10. This ensures secure and efficient data access, providing users with personalized and dynamic analytical experiences.

In this blog post, we will explore how to use the Token API for authenticating dashboard embedding in React-based applications, providing a step-by-step guide to implement access token securely.

Let’s get started.

Step 1: Create a React sample

1. First, open the command prompt. Ensure that the Node version is installed in your machine by using command node -v; this will display the version number of Node if it’s installed correctly.

node -v

2. Next, create a react sample using the command npx create-react-app FolderName to set up a new React application in the folder you choose.

npx create-react-app react-sample

3. After the React application has been created, open the react application in VS code using the code FolderName. Here, we have used the react-sample as our Folder Name.

code react-sample

Step 2: Create the Bold BI instance

1. Next, install the Bold BI Embedded SDK NPM package by using the command npm install @boldbi/boldbi-embedded-sdk in your terminal to add the necessary SDK to your project environment.

npm i @boldbi/boldbi-embedded-sdk@7.10.16

2. Next, install the dependent files by using the command npm install to fetch all required dependencies for your project.

npm install

3. Navigate to the \src folder and create a component named DashboardRendering along with a file named js. Within the DashboardRendering.js file, set up essential properties such as root URL, site identifier, dashboard ID, and token.

You can easily retrieve the root URL, site identifier, and dashboard ID by downloading the embed configuration file or the dashboard’s Get link option in Bold BI Server. For more details, refer to the Embed Settings – Embedded BI | Bold BI Documentation.

import React from 'react';
import ' .. /index';
import { BoldBI } from '@boldbi/boldbi-embedded-sdk';

//Rooturl of the BoldBI. This can be domain name/IP/Localhost along with the '/bi' at the end.
const rootUrl = "http://localhost:60011/bi";

//This is by defaul 'site/site1'. If you have created the new tenant in your onpremise version.
const siteidentifier = "site/site1";

//Unique Id of the Dashboard
const DashboardID = "352eb8e9-8a67-4f7a-a4e2-17d92fd7ca5b";

// Use the Token generated by using Server UI.
const access_token ="LCJJUCI6Ijo6MSIsImlzc3V1ZF9kYXRlIjoiMTcxOTU3MM.81i9G7N_DUy2fH41cRM"

Retrieving the Root URL, Site Identifier, and Dashboard ID from the Downloaded Conf FileTo obtain the access_token, you have the option to generate it from the Bold BI server UI or to use the REST API. You can check this documentation for further reference.

4. Implement the render() method to create the DOM elements and the componentDidMount() method to create the Bold BI instance and render the dashboard in DshboardRendering.js.

// Use the Token generated by using Server UI.
const access_token = "LCJJUCI6Ijo6MSIsImlzc3V1ZF9kYXRlIjoiMTcxOTU3MM.81i9G7N_DUy2fH41cRM"
class Dashboard extends React.Component {
    render() {
        return (
            <div id="DashboardRendering">
                <div id="dashboard"></div>
            </div>
        );
    }
    async componentDidMount() {
        this.dashboard = BoldBI.create({
            serverUrl: rootUrl + "/" + siteidentifier,
            dashboardId: DashboardID,
            embedContainerId: "dashboard",
            height: "800px",
            width: "1400px",
            token: access_token
        });
        this.dashboard.loadDashboard();
    }
}
export default Dashboard;

5. In the js folder, ensure the code imports the necessary modules. Also, define the App component to render the dashboard component and export it for use in other files.

import React from 'react';
import DashboardRendering from './DashboardRendering//DashboardRendering';
class App extends React.Component {
    render() {
        return (
            <div>
                <DashboardRendering />
            </div>
        );
    }
}
export default App;

Step 3: Run the embedding application

1. Before you can see your application in action, it’s essential to launch the React environment. Run the React application using the command npm start, and your development server will initialize.

npm start

2. Once the server is up and running, navigate to your web browser. The dashboard will render in the React application, providing you with a visual interface to interact with.

The limitations of Token API member support in JS embedding

Although the Token API member support in JS embedding offers many benefits in the world of embedded analytics, it does have some limitations. Here are some embedding modules that cannot be accessed using the Token authentication:

• Dashboard viewer or designer with dashboard name.
• Widget embedded with widget name.
• Edit data sources with the data source name.
• Views embedded with view name.
• Multiple widgets embedded with widget name.

It’s important to understand these drawbacks to make informed decisions when implementing this technology.

The following GIF image provides an overview of the Token API member support in a JS embedded application. Please check it to learn more on how to access the token in embedding.

Conclusion

I hope this blog has provided you with sufficient insight into embedding a Bold BI^® dashboard in a JavaScript application. By using the access token for embedding, you can seamlessly integrate dashboards not only in React embed applications, but also in those built with ASP.NET Core, ASP.NET MVC, ASP.NET, Node.js, and Angular. This support eliminates the need for making up an AuthorizeAPI endpoint for authorization, making the authentication process straightforward and efficient. For further details on embedding dashboards into your application, please refer to this blog and our documentation.

Get started with Bold BI now by signing up for a free trial based on your interest. If you have any questions about this blog, please don’t hesitate to leave a comment below. Additionally, you can reach out to us by submitting your support inquiries through the Bold BI website. If you already have an account, simply log in to submit your question.

Introduction

The date picker filter is an essential tool for anyone dealing with time-sensitive data, offering a simple solution for selecting dates and viewing the corresponding data. In this blog, we’ll explore the nuances of when and how to utilize a date picker in dashboards, the configuration process within Bold BI^®, and the essential features of date pickers that enhance data interaction. From best practices to real-world applications across various industries, we’ll explore the benefits of integrating a date picker into your data visualizations.

Understanding the date picker filter

A date picker filter is a user interface tool that allows users to select specific dates or date ranges from a calendar view. It is often used in forms, reports, and data dashboards. This interactive component streamlines data retrieval by filtering results according to the user’s chosen date parameters, improving analytical efficiency.

When to use a date picker in a dashboard

• Analyzing time-sensitive data.
• Comparing data across different time frames.
• Filtering data based on date ranges.

When not to use a date picker in a dashboard

• When you want to compare data from the previous year with the current year.
• The dashboard does not include time-sensitive data.
• The analysis does not require date-based comparisons or trend analysis.

How to configure a date picker filter in Bold BI

To configure data in the Date Picker widget in Bold BI, follow these steps:

1. Drag and drop the Date Picker widget from the toolbox into the dashboard design canvas.
2. Open the widget’s Properties and navigate to Assign Data.
3. Drag and drop the date column from the Dimension section to the Column(s) section.

For more details on how to configure the Date Picker widget in Bold BI, refer to our documentation.

6 Key features of the Date Picker in Bold BI

Incorporating the Date Picker widget in a Bold BI dashboard delivers the right features to significantly enhance the user experience. Let’s explore these six key features of the Bold BI Date Picker visuals:

Range selection

The range selection feature of the Date Picker lets users select a range of dates by picking start and end dates. By turning this feature off, only a single date can be chosen.

Limit date range

This feature allows you to display a limited range of dates in the Date Picker. Dates outside this specified range are automatically unavailable, restricting user interaction. By default, this option is turned on.

Fixed calendar selection

The fixed calendar selection feature, shown when the range option is turned on, forces users to choose a start date from the left calendar and an end date from the right calendar without discarding any previous selection.

Highlight available dates

This feature highlights selectable dates in the Date Picker, making it easier for users to see which days they can choose, streamlining the selection process.

Select today as the default

This feature sets today’s date as the default selection in the Date Picker so users can quickly proceed with analysis that is based on the current date.

Show latest date

This feature configures the Date Picker visual to highlight or automatically navigate to the most recent date available for selection. It’s beneficial when analysis is urgent, such as in a dashboard displaying the latest data entry or a report update.

To learn more about these features of the Date Picker visual in Bold BI, refer to our documentation.

Best practices for using a Date Picker in dashboards

• Highlight available dates: This helps users instantly identify and select dates that have data available.

• Limit dates: Allow users to make decisions and filter data within a predefined time frame.

• Confirm selections before applying: Provide a clear Apply button for users to confirm their date range selections before the corresponding data is visualized.
• Current date default: Set the default selection to the current date to provide users with immediate and relevant information.

Use cases for a Date Picker filter

Date picker filters in dashboards let users analyze their data from precise periods of time. Let’s see how various sectors utilize this potent tool.

Human resources: Training dashboard

The date picker filter in the HR Training Dashboard allows HR staff to track the progress of employee training programs over specified time periods. This functionality helps identify training trends and effectiveness, assess compliance with mandatory training, and schedule future sessions more effectively.

Healthcare: Patient experience analysis dashboard

The date picker filter in the Patient Experience Analysis Dashboard helps administrators monitor patient satisfaction scores over various time frames. By analyzing data across time, providers can implement targeted improvements to enhance patient experience.

Finance: Stax Bill subscription management dashboard

For the finance industry, the date picker filter within the Stax Bill Subscription Management Dashboard enables teams to monitor subscription trends, renewals, and cancellations over selected periods. This helps in understanding customer behavior and planning effective marketing strategies.

Information technology: Asana project management dashboard

For IT, the date picker filter in the Asana Project Management Dashboard is essential for tracking project progress and task completion rates over time. Project managers can use this feature to ensure timely delivery of tasks and improve resource allocation.

These are just a few examples of how a Date Picker can be utilized across various industries to streamline analysis and enhance dashboard user experiences. By creating your own dashboards with Bold BI and incorporating the Date Picker widget, you can customize your analysis and data visualization needs to suit your unique scenarios.

Conclusion

In summary, adding a date picker in dashboards significantly improves the user experience by allowing for easy, fast selection and filtering of time-sensitive information. Experience the convenience of choosing exact dates for your data analysis by using a date picker filter.

Don’t miss out on important insights—discover how Bold BI^® can transform your data analysis methods by registering for a free trial today!

Introduction

In user interface design, the list box is an essential element for giving users a way to select items. It is an especially useful tool in dashboards. With it, dashboard designers can list multiple items in one place, preserving valuable screen space and simplifying user selections. In this blog, we will explore the list box, its configuration in Bold BI^®, best practices for using it, and a few use cases.

Understanding the list box visual

A list box is a graphical element that displays a list of items. It is often used to allow users to select or filter items and reflect that selection in other visualizations.

How to configure a list box visual in Bold BI

1. In the Dashboard Designer, drag and drop the List Box widget from the visualization panel to the design canvas.
2. Click the Settings icon on the widget. This will open the Properties panel.
3. In the Basic Settings group, select the Enable Multiselect option to allow the widget to be used for filter selection.
4. Assign data to the widget and customize it as needed.
5. Preview the widget and adjust its settings for clarity and visual appeal.

The following GIF shows the configuration process.

To learn more about the configuration process, read our documentation.

When to use a list box visual

• Selecting categorical data.
• Filtering a large dataset.
• Selecting multiple items simultaneously.
• Displaying items of similar data type.

When not to use a list box visual

• Presenting lengthy content.
• Providing limited options.
• Presenting complex or hierarchical data.
• Visualizing quantitative data.

Best practices for using a list box in dashboard

• Keep it simple: Use clear, concise content for the list box items so that users understand the options clearly.
• Enable multiselection: If the context requires it, allow users to select multiple items.
• Sorting: Arrange items logically—alphabetically, numerically, or by frequency or relevance.
• Default selection: Enable a default selection. This gives users a starting point for working with the widget.

Use cases for a list box in dashboard

Let’s take a look at how list boxes are used in several sample Bold BI dashboards.

Sales

The Sales Performance Dashboard’s list box facilitates efficient visualization of product categories across the other widgets in the dashboard. With it, sales teams can quickly select and analyze data. The list box lists the product categories that can be visualized in the other widgets. Any combination of categories can be selected simultaneously in the list box. The dashboard with all categories in the list box selected is shown in the following figure.

Surveys

The list box in our SurveyMonkey Survey Overview Dashboard lets surveyors choose which survey data to visualize in the dashboard. With it, they can quickly switch between data sets to analyze response rates for various surveys. The following figure shows the survey dashboard with all available surveys selected in the list box and the corresponding data visualized in the other widgets.

Property management

In our Property Management Dashboard, the list box allows property managers to easily select the properties whose data they want to visualize and inspect. The dashboard provides insights into gross income, net income, and tenant turnover rates, making it easier to monitor tenant satisfaction and overall income. The following figure shows the dashboard with just a few properties selected in the list box.

Education

In our Higher Education Enrollment and Retention Dashboard, the list box lets administrators choose fields of study whose data they want to analyze. The dashboard provides insights on admission rates, enrollment, and retention rates so that campus resources can be efficiently allocated. The following figure showcases the dashboard with just one field of study selected in the list box.

Conclusion

A list box in a dashboard gives users intuitive selection and filtering interfaces, encouraging data exploration and analysis. Explore the capabilities of list boxes in dashboards today with a free trial of Bold BI^®. For more information, visit our website or contact our support team.

Introduction

As organizations grapple with complex data challenges, their data analysts navigate a labyrinth of decisions. Faced with the choice to publish (online migration) or migrate (offline migration) their dashboards, analysts weigh the benefits and shortcomings of each. This article demystifies the decision-making process behind choosing to publish or migrate dashboards, outlining the strategic purposes behind each. Choosing the right one can streamline your organization’s analytical reporting to deliver critical insights to stakeholders.

Why publish or migrate a dashboard?

Accessibility and insight-sharing

Publishing a dashboard allows for broader accessibility to important data insights across an organization or with external stakeholders. This ensures that decision-makers, team members, and clients can easily access up-to-date information, facilitating a transparent and informed decision-making process. The shared insights help align teams toward common goals and objectives based on real-time data.

Data governance and security

When migrating and publishing dashboards, data governance and security measures can be more effectively applied and managed. By controlling who has access to what information, organizations can ensure that sensitive data is only accessible to authorized users. This is crucial for compliance with data protection regulations and for maintaining the integrity and confidentiality of the data.

Improved collaboration

Both published and migrated dashboards encourage collaboration within teams and departments. It enables users to work on the same set of data, share insights, and make collective, informed decisions. This collaborative environment can lead to more innovative solutions to business challenges and a more cohesive approach to reaching organizational goals.

Efficiency and time-savings

Migrating and publishing dashboards streamline the reporting and analysis process. Instead of manually compiling reports from various data sources, a dashboard provides a centralized platform for accessing and analyzing data. This saves significant time and resources, allowing employees to focus on more strategic tasks rather than on repetitive data compilation and reporting.

Performance monitoring and real-time updates

With published and migrated dashboards, organizations can monitor key performance indicators in real time. This immediate access to performance data allows for quick identification of trends, issues, and opportunities. Consequently, businesses can respond more swiftly and effectively to market changes, operational challenges, or customer needs, thus maintaining a competitive edge.

How to publish a dashboard in Bold BI

Bold BI^® makes it easy to publish your dashboards after designing them. Depending on where your target audience is, you can publish them internally to sites on the same Bold BI server, or externally to other Bold BI servers.

The following steps show how to publish a sample dashboard to different sites created in the same Bold BI server.

Publishing a dashboard internally

1. In the Dashboards list, click the three-dot action button for the dashboard you want to publish and then select Publish.

   

2. In the dialog that appears, select Internal Site and click Next.
   

   

3. Fill in the required details and then click Submit.

   

4. Navigate to the other site and view the dashboard.

   

To learn more about this process, refer to our documentation.

How to migrate a Bold BI dashboard to another tenant

Bold BI also supports dashboard migration, which allows you to transfer your dashboards from one tenant to another via online and offline migration. The offline migration relies on a BBIX file that you download and upload from the source to the destination environment.

To learn more about Bold BI’s migration feature, read our blog, “Streamlining Dashboard Migration Across Tenants In Bold BI^®.” It provides a clear illustration of the process.

When to publish and when to migrate a dashboard

Accessibility: The biggest factor in deciding to publish or migrate a dashboard is what the dashboard’s audience has access to. If the intended audience has access to the application in which the dashboard is embedded and maintained, then you should publish the dashboard. If the audience is a set of external stakeholders outside of the organization, it is likely that you will need to restore to migrating the dashboard.

Ease of sharing: If sharing with ease is your goal, publishing is the way to go. With just a URL or embed code, anyone can view your dashboard. When migrating a dashboard, access will likely be restricted to individuals who have permissions in the new platform.

Interactivity: For an interactive experience that allows for in-depth data exploration, publishing your dashboard is ideal. In contrast, a migrated dashboard’s interactivity might be limited depending on the viewing tools.

Real-time updates: When you need to ensure that your dashboard displays the latest data without manual refreshes, publishing is the answer. With migration, you must verify that the target platform can handle real-time data.

Conclusion

The decision to publish or migrate a dashboard directly affects who has access to the dashboard’s analysis and insights. Carefully consider who needs to view the dashboard and what applications and interfaces they have access to. Furthermore, think about the features you want to support in the dashboard, as many features that are available in a published dashboard may not be supported in a migrated dashboard.

If you have any questions or need assistance, don’t hesitate to reach out through the Bold BI website; simply log in to submit your inquiries if you already have an account. If you’re not yet a customer, get started with Bold BI now by signing up for a free trial!