What is a Dashboard

What is a Dashboard – A Complete Overview

Dashboard is an interactive front-end of a data analytics solution that gathers and visualises data from one or more sources, facilitating quick analysis and well-informed decision-making. Dashboards are important tools for businesses in an environment where data is used to monitor and track operational or business performance because they give a detailed view of important metrics and performance indicators. Dashboards, unlike static reports, generate insights that let users monitor trends, spot anomalies, and delve into specifics.

Dashboards serve a variety of sectors and purposes, whether they are utilized for assessing strategic objectives, analysing sales performance, or keeping an eye on IT infrastructure health. They are crucial for improving operational effectiveness and fostering corporate success because of their capacity to translate complex data into easily understood representations.

This article provides a thorough guide for dashboard users by examining what dashboards are, their essential elements, types, advantages, best practices, and upcoming trends.

Understanding Types of Dashboards

Dashboards can be categorised into three broad categories:

1. Operational dashboard
2. Analytical dashboard
3. Strategic dashboard

1. Operational Dashboard

These are real-time dashboards that are used to monitor processes and systems. For example, Zabbix is an open-source software that is used to monitor IT infrastructure such as servers, networks, virtual machines and cloud services. With the help of Zabbix, you can create operational dashboards that provide real-time trends of CPU usage, data transfer rate, RAM usage, storage usage, etc.

2. Analytical Dashboard

Analytical dashboards are aimed at generating insights from the data, they provide in-depth trend analysis, slicing and dicing of data to a very detailed level. For example, a dashboard for a Fraud Detection system will provide you with details of possible fraudulent transactions, customers involved in those transactions and other details that will allow an analyst to validate if actual fraud happened or if it was a false-positive transaction.

3. Strategic Dashboard

As the name suggests, these dashboards provide high-level business and operational information to senior business executives or decision-makers. For example, tracking monthly or weekly sales and identifying the need to drop the product which has not been selling from the portfolio.

Key Elements of a Dashboard

A dashboard for an analyst is the same as a canvas for a painter. Though it is up to the creativity of the analyst how she makes the dashboard look both professional and artistic, there are some key elements that are essential to a dashboard, whatever the design.


Charts and graphs are the core of any dashboard which converts data into graphical representations such as maps, tables, bar graphs, pie charts, etc.

Key Performance Indicators

These are the metrics that reflect the performance and track the progress of the business towards its goals. KPIs are generally represented just as the number on the dashboard, for example, the number of new customers in the month, total sales in the month, percentage change in sales from the previous month, etc.


Filters differentiate dashboards from static reports. They bring interactivity to the dashboards as they allow the users to customise the view on the dashboards as per their requirements, for example, product categories, geographical areas, dates, drill-down capabilities, etc. Filters add the capability to explore the data in more detail.

Best Practices for Designing Effective Dashboards

Data visualisation is about storytelling through data and dashboards allow you to present a complete story with help of data using interactive filters. To guarantee that a dashboard effectively communicates the story and serves the needs of its users, careful design is necessary. Consider the following best practices:

Keep it Simple and Focused

Information should be presented on a dashboard in an understandable and efficient way. Keep things simple by concentrating on the metrics and visualizations that matter most. Every component ought to have a distinct function, and extraneous information ought to be kept to a minimum to avoid confusing the user.

Use Appropriate Visualisations

Select the suitable visualization type based on the analysis you are displaying. You can get creative with doughnut charts, box plots, tree maps, speedometers, etc. However, you should know which chart is the most effective in which case, for example, to show track a metric against date line graphs are the best, and to show the relationship between two variables scatter chart is the best. Make sure the data is appropriately represented and the visuals are simple to understand.

Ensure Data Accuracy and Relevance

The data on the dashboard needs to be accurate, up-to-date, and relevant to the needs of the users. Make sure the data sources are updated frequently and the material is accurate to maintain people’s trust in the dashboard’s findings.

Design for the End-User

Determine who the dashboard’s target audience is and what their needs and preferences are. Adapt the design to suit their specific requirements, whether they are executives in need of high-level summaries or analysts in need of in-depth drill-down capabilities. The dashboard’s overall effectiveness is increased by user-friendly interfaces.

Make It Interactive and Customizable

Include interactive elements such as drill-downs, filters, and dynamic data selections that allow users to delve deeper into the data. Users are able to customize their dashboards to meet their own needs and preferences.

Maintain Consistency

To give the dashboard a unified and polished look, use similar layouts, colours, and typefaces. Consistency facilitates rapid dashboard navigation and understanding for users.

Provide Context

Always provide context for the data being displayed. Include titles, labels, and legends to help users understand what they are looking at. Annotations and explanations can also add valuable context, especially for complex data sets.

Optimize for Performance

Ensure that the dashboard loads quickly and performs well, even with large datasets. Efficient data processing and optimized queries are crucial to providing a smooth user experience.
By adhering to these best practices, you may design dashboards that are highly functional and aesthetically pleasing, improving business intelligence overall and promoting improved decision-making.

Common Challenges

Creating dashboards comes with its own set of challenges. These challenges are important to understand and crucial in ensuring that dashboards always remain accurate and relevant.

Integration with Data Source

The most important part before preparing a dashboard is to connect the visualisation tool with the data source. Most of the time, the dashboards are connected to a database, with one or more tables. Most of the database tables contain a large number of fields while the dashboard requires only a few of them, hence, one should always try to bring in the data that is to be used for creating the dashboard and exclude all the data that is not needed. This improves the performance of the dashboard and also prevents the visualisation tool from slow processing due to a large dataset.

Hard-coding the Values

Visualisation tools allow developers to create new columns or measures that would be used in the dashboard. The analyst creating the dashboard should avoid hard-coding any values in the manually created columns. In case the data gets refreshed, and a new value comes up in the new data, the hard-coded value would become incorrect and make the whole dashboard inaccurate which can lead to wrong decisions made on the basis of wrong data.

Updating the Dashboard

Business requirements may change over time, hence, the information available in the dashboard would require to be updated with new charts, new analysis or may be a completely ne dashboard. The analyst should regularly review and update the dashboards by taking feedback from the users and look for the areas of improvement and enhancement.

Tools for Creating Dashboard

There are several tools available for visualisation and creating dashboards. The selection of tool depends upon the type of dashboard one wants to create (operational vs analytical) and what functionalities are required in the dashboards.

Here are some popular dashboard tools.

MS Excel

Though many won’t consider Excel as a tool for creating dashboards, many organisations like SMEs and even large organisations dealing with low volume of data still prefer Excel for reporting and dashboarding. Excel provides great visualisation functionality when data size is not big. You can create customised visualisations, tables and dashboards in Excel to prepare and regularly update the reports for decision-makers. However, Excel is not the go-to tool when the data comes in large volumes.


Tableau is one of the simplest and easy to use tools for developing dashboards. Simple drag and drop user interface allows the analysts to quickly create great visuals from the data. Tableau is a powerful tool which provides options to connect to various proprietary database and can handle large datasets easily. It allows easy sharing of dashboards with ability to extract underlying data for further analysis.

MS Power BI

Power BI integrates easily with Microsoft as well as other data sources and products. It provides wide range of visualisation options. It is affordable, offers free desktop version unlike Tableau.

Qlik Sense

Like Tableau and Power BI, Qlik also provides wide range of visualisation options. It also provides associative data indexing, enabling users to explore data intuitively.


Dashboards are crucial in the data-driven world of today because they convert unprocessed data into insights that can be used to make wise decisions. They let companies effectively visualize, analyse, and comprehend data. In order to create effective visualizations that satisfy a variety of user needs, it is imperative to understand the essential elements, types, and best practices for dashboard design. Even though there are obstacles like poor data quality and low user uptake, they can be overcome with the right plans and tools. Numerous options are available for putting robust dashboard solutions into practice with tools like Tableau, Power BI, and others.

Dashboards will become more valuable as technology develops by including elements like artificial intelligence and real-time data processing. Organizations may use data to drive success and keep a competitive edge by adopting these technologies and best practices.

To help you gain complete knowledge of Data Analytics and Dashboarding, Techcanvass offers a range of specialized courses like

1. Data Analytics Certification Training
2. IIBA Data Analytics Training(CBDA)
3. Data Analytics Fundamentals Course
4. Data Visualization Training in Tableau

These courses are tailored to provide you with comprehensive training, ensuring you are well-prepared to meet industry demands and excel in your data analytics career.

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