Dashboards

• Improve time to Insights

• Dashboards & Reporting frameworks

• Self-Service Analytics

Creating an analytics dashboard involves several steps, from gathering data to designing and implementing the user interface.

Here's a step-by-step guide to building an analytics dashboard:

1. Define Objectives: Determine the goals and objectives of the dashboard. What insights do you want to provide to users? What key performance indicators (KPIs) or metrics will be displayed?

2. Gather Data: Collect the data needed to populate the dashboard. This may include data from various sources such as databases, APIs, logs, spreadsheets, or third-party services.

   Ensure that the data is clean, structured, and relevant to the dashboard objectives.

3. Data Preparation and Modeling: Clean, transform, and preprocess the data as needed

   for analysis. Perform any necessary calculations, aggregations, or data modeling to derive

   meaningful insights. Consider using tools like SQL, Python, or R for data preparation.

4. Choose Visualization Tools: Select the appropriate visualization tools and techniques to

   present the data in an easily understandable and visually appealing format. Common

   visualization types include charts, graphs, tables, maps, and gauges. Choose tools like

   Tableau, Power BI, or custom JavaScript libraries based on your requirements.

5. Design Dashboard Layout: Design the layout and structure of the dashboard to effectively communicate insights and facilitate user interaction. Arrange visualizations

   logically, grouping related information together. Consider the hierarchy of information and

   prioritize the most important insights.

6. Implement Interactivity: Enhance the dashboard with interactive features to enable users

   to explore the data dynamically. Add filters, drill-down capabilities, tooltips, and hover

   effects to allow users to interact with visualizations and explore data from different

   perspectives.

7. Dashboard Development: Develop the dashboard using chosen visualization tools or

   custom web development techniques. Implement the designed layout, visualizations, and

   interactive features according to specifications.

   
   

8. Test and Iterate: Test the dashboard to ensure that it functions as intended and provides

   accurate insights. Solicit feedback from users and stakeholders to identify areas for

   improvement. Iterate on the design and functionality based on user feedback and testing

   results.

9. Deployment: Deploy the dashboard to a production environment where users can access

   it securely. Ensure that the dashboard is hosted on a reliable server with appropriate access controls and security measures in place.

   
   

10. Maintenance and Updates: Regularly maintain and update the dashboard to keep it

    current and relevant. Monitor data sources for changes, update visualizations as needed,

    and address any issues or bugs that arise. Continuously iterate and improve the

    dashboard based on user feedback and evolving requirements.

By following these steps, our team can create an effective analytics dashboard that provides

valuable insights to users and supports data-driven decision-making within your organization.