What is a Dashboard in Data Analytics ?

Understanding data is the key to making the best decisions for any organization in today’s world. However, even the most data-savvy individual might get overwhelmed by the amount of information available at any one time. Creating a dashboard that conveniently shows all of your data visualizations in one location is one of the simplest methods to make data easy for technical and non-technical users to grasp.

In this article, we will discuss Dashboards, Types of Data Analytics Dashboards, Use Cases, Tools, and Steps to Create a Dashboard in Power BI.

What is Dashboard in data analytics?

Understanding Dashboard

A data analytics dashboard is a tool for multitasking, organizing, visualizing, analyzing, and tracking data. A data analytics dashboard’s ultimate goal is to make it simpler for data analysts, decision makers, and ordinary users to comprehend their data, get deeper insights, and make better data-driven decisions.

Data dashboards are intended to integrate and extract critical information from a wide range of data sources, services, and APIs. Visuals like as charts, figures, graphs, and tables are used to provide this information in a single, cohesive manner. A company may have a distinct customisable dashboard for each department and even a dashboard for each particular project, allowing for more detailed monitoring of extremely specific KPIs.

Types of Data Analytics Dashboards

Data analytics dashboards are classified into three types: operational, strategic, and analytical.

1. Operational analytics dashboards are concerned with the progress of work and the present status of operations. Real-time operational dashboards are frequently used to understand where issues exist and are less frequently utilised to go further into data.
2. Strategic analytics dashboards present KPIs as well as concise, at-a-glance data visualisations. The emphasis is on displaying straightforward trends and progress, gaining rapid responses, and assisting users in monitoring and understanding if KPIs are on track.
3. Analytical dashboards place a premium on flexibility, allowing users to investigate data points in as many different ways as possible, using filters and comparisons to uncover hidden insights. Drill-downs, prediction models, and what-if parameters are all common aspects.

Use Cases of Dashboards in Data Analytics

• Monitoring critical company KPIs and performance indicators in order to make educated decisions and drive strategy.
• Monitoring financial data, budgets, and predictions to aid in financial planning and decision-making.
• Marketing analytics is the study of marketing campaigns, consumer behaviour, and conversion rates in order to improve marketing strategy.
• Monitoring operational data, supply chain performance, and manufacturing efficiency in real time to detect and rectify concerns.
• The study of human resource measures such as employee turnover, performance, and workforce demographics.

Dashboards are extremely adaptable aggregation and visualisation tools used by professionals to analyse complicated data or subject matter experts to track or show data to non-subject matter experts. Use them in presentations to CEOs or other important stakeholders to assist them understand the issues, opportunities, and areas for growth and change.

The significance of dashboards

Dashboards are useful because they enable users to make better, more informed, data-driven decisions. They help you obtain a more accurate, in-the-moment grasp of what’s occurring in the environment around you and negotiate quick, often challenging changes since they’re dynamic, interactive, and present near real-time data.

What Are the Most Effective Analytics Dashboard Tools?

The best data analytics dashboard tools will include the following features: the ability to connect data from multiple sources, embedding capabilities, self-service reporting, automated real-time updates, streaming and predictive analytics powered by AI, filtering across time and location, interactive visual analytics, full customisation, and at-a-click exploration. HEAVY’s visual analytics platform, Izenda, Periscope Data, Dundas BI analytics dashboard, Microsoft Power BI, IBM Cognos, TIBCO Spotfire, Looker, and Sisense are a few examples of prominent corporate analytics dashboard software.

How to create a dashboard in Power BI?

Creating a dashboard with Power BI entails numerous processes, beginning with importing and converting data and progressing to developing visualisations and publishing the completed dashboard. A step-by-step approach on creating a simple Power BI dashboard is provided below:

Step 1

1. Download and install Power BI Desktop.
2. Power BI Desktop, a free programme for producing reports and dashboards, should be downloaded and installed.

Step 2

1. Data Import
2. Launch Power BI Desktop.
3. In the Home tab, press the “Get Data” button.
4. Select a data source (Excel, SQL Server, CSV, and so on).
5. Import the information into Power BI.

Step 3

1. Data Transformation
2. You may clean and manipulate your data with the Power Query Editor.
3. Remove superfluous columns, deal with missing values, and execute other data cleansing operations.
4. To save your changes and return to Power BI, click the “Close & Apply” button.

Step 4

1. Design Visualisations
2. Navigate to the “Visualisations” window in Power BI Desktop.
3. Choose the sort of visualisation you want (for example, a bar chart, a pie chart, a table, etc.).
4. To define the axes and values, drag and drop fields from your dataset into the visualisation.

Step 5

1. Format and Design
2. Format your visualisations using the formatting choices in the “Visualisations” tab.
3. Colours, labels, and other attributes can be changed to improve the visual attractiveness of your dashboard.

Step 6

1. Optionally, create multiple pages.
2. If your dashboard requires many pages, under the Pages pane, click the “New Page” option.
3. For each page, repeat the process of importing data, producing visualisations, and formatting.

Step 7

1. Make Relationships (If You’re Using Multiple Data Tables)
2. If your dataset has numerous tables, specify relationships between them so that cross-filtering is possible.
3. To access the relationship view and build relationships between tables, click the “Model” icon.

Step 8

1. Set Up Visualisations
2. Visualisations may be dragged and dropped onto the canvas.
3. Resize and position them to create an eye-catching pattern.

Step 9

1. Design a Dashboard
2. In the “Home” page, click the “New Dashboard” button.
3. Give your dashboard a name and save it to your workspace.

Step 10

1. Pin Dashboard Visualisations
2. Choose a visualisation from the canvas.
3. In the top-right corner, choose the “Pin Visual” symbol.
4. Select the dashboard to which you wish to pin the visualisation.

Step 11

1. Save and publish your work.
2. Make a backup of your Power BI Desktop file.
3. To save your dashboard to the Power BI service, click the “Publish” button.

Step 12

1. Collaborate and Share
2. Activate the Power BI service.
3. By publishing your dashboard to the Power BI service, you may share it with others.
4. Share the dashboard URL with your team or embed it in other programmes to collaborate.

This is an introduction to generating a Power BI dashboard. Depending on your individual requirements and the intricacy of your data, the procedure might get more complicated. Power BI has a plethora of tools and capabilities for sophisticated analytics and reporting.

Conclusion

Each data analytics dashboard will seem different based on the aims and objectives of each project. The optimal solution will be one that allows you to be one with your data and engage with it quickly and easily.