Any good Business Intelligence (BI) dashboard represents data visually in a form that is easy to understand by key decision-makers in an organization. It displays complex information in a simple format, enabling them to identify patterns, developments, and inconsistencies in the business.
Older versions of business dashboards offered their services with the help of data analytics tools. However, the latest Business Intelligence (BI) dashboard services are being provided through workflows and applications to meet business and data requirements. Designing a competent dashboard using the best tips and tricks results from an all-inclusive Business Intelligence (BI) process. It includes numerous processes such as requirements gathering, outlining Key Performance Indicators (KPIs), and building a model for data. Moreover, the process of building a good dashboard should not be underestimated since a poorly designed dashboard could lead to incorrect or partial insights.
This article will help you understand the steps, practices, and critical templates for building impeccable Sisense dashboards that will help you improve the performance of your business exponentially.
Table of Contents
Introduction to Sisense
Sisense is a popular Data Analytics and Business Intelligence tool that integrates seamlessly with the Sisense platform. It gives users the ability to perform advanced analysis on their data and derive actionable insights. It provides a single, cohesive User Interface for users to store, analyze and visualize their data efficiently for better decision-making.
In addition, it allows users with or without coding knowledge to produce, consume and share insights intuitively with each other. Sisense goes beyond the dashboard by providing an Artificial Intelligence (AI) driven platform that can help businesses drive better and faster decisions, improving customer experience exponentially. Sisense is now used by almost 2,000 global businesses such as Tinder, GE, Nasdaq, GitLab, Rolls Royce, Philips Healthcare, etc., to innovate, disrupt markets and drive meaningful change in the world.
More information about Sisense can be found here.
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Let’s look at Some Salient Features of Hevo:
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- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
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- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
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- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Features to Look for in Perfect Sisense Dashboards
The various features that should ideally look for in perfect Sisense Dashboards are as follows:
- Transformations from Complex to Easy: The amount of data is enormous, constantly changing, and evolving; therefore, it requires different techniques for analysis. The Sisense Dashboards should remove all kinds of data complexity and transform it into a simple form.
- Provides Clarity: The Sisense Dashboards should establish a meaningful connection with data. Visual representation of data is a critical aspect of a dashboard.
- Provides Meaning to Data: The insights derived from the data depend entirely on the choice of data visualization. The data visualization needs to be such that it represents the extracted information correctly.
- Provides Necessary Details: The goal associated with perfect Sisense Dashboards is to offer every viewer easy access to data as needed and hide unnecessary information simultaneously.
Understanding User Requirement
Well-structured Sisense Dashboards offer solutions to business problems and assist decision-makers with instant analysis and feedback. The first step in designing an efficient Sisense Dashboard is determining the clientele and what information they want to view. In order to understand what information your dashboards should include, you should identify the role of your users (executive, administrative, or marketing) and understand their knowledge of business and experience with data. This information will help you decide the number of dashboards required by your user and the type of data to show in each.
Available Data and Actions to Be Performed
Once you have an understanding of the users, you have to collect information regarding their particular requirements. For this, you need to know the following things about the available data:
- The type of data your users will view in the Sisense Dashboards.
- Whether the data is in the form of summary highlights or broken down into granular form.
- The time period over which the data was collected.
- Whether you need to go through data from the backdate or recent outcomes are sufficient.
You also need the following information about the actions being performed:
- The decisions your users will make depending upon the dashboard.
- The type of Key Performance Indicators (KPIs) being considered by your users.
- Quality of research needed by them to back their decisions.
- Whether filtering or refining of data is required.
Bad Design Choices for Sisense Dashboards
The key issues that you need to keep in mind while building perfect Sisense Dashboards are as follows:
- Having widgets more than the required limit (maximum 30) might confuse viewers.
- Response time for simple queries should not take more than 5 seconds.
- Lack of structure or organization skills reflects on the visual layout, which does not go down well with the viewers.
- Adding tables do not contribute much to insights.
Generating a Logical Outline for Sisense Dashboards
Logically structuring your Sisense Dashboards will provide better clarity to your users and can be done by implementing the following guidelines:
1) Arranging Information in the Form of Inverted Pyramid
A good organizing principle to implement on your Sisense Dashboards is the Inverted Pyramid. This method specifies that the essential data is given priority and positioned at the top, while less critical information is placed below.
The following list shows the order to be followed when using the Inverted Pyramid method:
- Placing most significant data such as Gauges or Key Performance Indicators (KPIs) on the top.
- Identifying the essential facts that would improve the user’s understanding, such as common trends at the second position.
- Finally, position the background data used by viewers to understand more about the context.
2) Picking the Correct Mode for Visuals
The choice of visual aids to visualize your data plays an essential role in making Structured Sisense Dashboards. Identifying the kind of visualization to use for every business query can be tricky. Therefore, all data being visualized should fall under one of the four following pillars of data visualization:
Comparison of data points is one of the most widely used and easy-to-understand methods for data visualization. As the name suggests, Comparison Visualizations are used to evaluate and compare values of two or more data points. Comparison Visualizations include Column Chart, Bar Chart, Line Graph, Time-line, etc.
The Composition Visualizations are leveraged to show how individual parts of a metric combine to make up the whole and displaying them as a sum. Composition Visualizations can also be used to show how a total value can be divided into parts and highlight each part’s significance relative to the total value. Composition Visualizations are typically created using Stacked Bars or Columns, Pie or Donut Charts, Stacked Area Charts, Waterfall Charts, etc.
Distribution Visualizations combine the functionalities and merits of both Composition and Comparison Visualizations. It can help you visualize related or unrelated data points by examining the entire data spectrum. Distribution Visualizations can be used to identify trends, correlations, patterns, clusters, shapes, averages, outliers, etc. Distribution Visualizations are typically created using Column and Bar Histogram Charts, Line and Area Charts, Scatter Plots, Map charts, etc.
Relationship Visualizations are used to show the relationship, correlation, or connection of two or more variables and their properties. Relationship Visualizations are typically created using Scatter plots with two dimensions, Bubble Charts with three to four dimensions using bubble size and color scale, or five dimensions with animation or layers, Line Chart with two or more axes, Table Charts, etc.
3) Strategizing Visualizations to Highlight Vitals Points
Well-designed Sisense Dashboards will show the users critical points at a glance. You can use the following design practices to highlight the vital issues for users:
A) Decreasing Confusion in Visuals
The design of Sisense Dashboards should be minimalistic and display only the required information. Therefore, only the essential visualizations should be added. When confronted with design issues, it is better to pause and think whether the new element being included will benefit the user in deriving insights from the visualizations or not. Users can ensure a minimalistic dashboard by ensuring the following:
- Every dashboard must have at most 5-9 visualizations.
- Stuffing as many facts as possible in the dashboard is not a good practice.
- Exceeding the limit creates confusion and distracts users from the dashboard’s purpose.
- It can be avoided using filters and hierarchies.
- If more visualizations are to be included, it is advised to split your dashboard into two or more distinct dashboards.
B) Using Filters and Hierarchies
Filters offer data-filtering choices that change the data shown in your widgets as per requirements. Viewers can choose specific filters to show only the subsections of data relating to these filters. Filtering helps your users focus on specific data in a large dataset.
Through Filters, viewers can break down across any value in the widget. Although Filters can be extremely useful, too many filters might distract viewers and might send them to drill-down routes that do not contribute to the analysis. Hierarchies can be added to your Sisense Dashboards to solve this issue so that viewers can select the correct drill-down route and access data across predefined drill hierarchies only.
C) Using a Consistent Palette
Using a stable Color Palette allows highlighting essential data, reduces visual confusion, and enhances appearance. You can also use Sisense’s predefined color themes if you are not well-versed with design concepts. Using them, you can quickly generate impressionable visuals.
D) Using Plugins
Plugins are used to add specific properties and enhance the operability of the main product. Sisense offers plugins that are suitable means to layer data in your widgets. Some of the most popular and useful Sisense Plugins are as follows:
- Accordion: Allows users to select an indicator widget to enlarge a sub-dashboard. This plugin helps in providing vast amounts of data within restricted space.
- Jump to Dashboard: It can be selected through a new tab or popup window. It is suitable for displaying added information about particular series on demand.
- Tabber: This plugin helps switch between views to show different parts of data without modifying Sisense Dashboards.
- ToolTip: Shows values as added information on the Column Chart instead of displaying them as columns.
This article provided you with a comprehensive understanding of how you can easily build impeccable Sisense Dashboards. In addition, it also provided you a list of strategies that can be leveraged to make your Sisense Dashboards easy to understand.
Choosing a Business Intelligence and Data Analysis tool for your business can be a tough decision primarily because almost all departments in a business such as Product, Finance, Marketing, etc. now make use of multiple platforms to run their day-to-day operations and there is no single tool that can integrate with all these sources easily. Hence, businesses can consider using automated Data Integration platforms like Hevo.
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Hevo helps you directly transfer data from a source of your choice to a Data Warehouse, Business Intelligence tools such as Sisense, etc., or desired destination in a fully automated and secure manner without having to write the code. It will make your life easier and make data migration hassle-free. It is User-Friendly, Reliable, and Secure.
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