Creating Interactive Data Science Dashboards in Excel without Streamlit

Shamima Sultana | Alayaran.com

In a surprising turn of events, Excel has emerged as a powerful platform for creating interactive data visualizations, rivaling popular data science web apps like Streamlit. Using built-in Excel features, users can build dynamic dashboards that provide real-time insights into their data.

A recent tutorial by ExcelDemy revealed the process of constructing these dashboards in just minutes without Python coding skills required for a beginner-level knowledge user. This makes analyzing various data sets accessible to anyone, regardless of previous expertise level with excel's most innovative features.

To begin building an dashboard like this here are our step-by-step processes below:

Step 1: Prepare Dataset

Users can quickly format the Excel file by using the tools available like getting data from CSV or other file types. Additionally formatting and making cleanup for large datasets is advisable to avoid errors and performance issues.

Converting Data To A Table

Tables enable more precise management of formulas with pivot tables used at later stages to organize data in specific ways as per their needs.

1- Select entire Dataset 2- Open Table Tab 3- Click on Create Table (Ctrl T or 'Insert Table') 4- Choose headers and create dynamic tables where users will insert new tables at required position

Step 2: Creating Interactive PivotTables

These tables are vital in providing the first layer of visual analysis.

1. Selecting A Data field (SalesData table) 2- Open Insert Tab 3- Select pivot Table button (Ctrl R or 'Insert PivotTable') 4- Choose a new empty Worksheet tab for the new data

Create PivotTables :

For Sales Revenue: - Create second Pivot table by selecting all available Sales fields

Regional Analysis, Product categories and KPIs are created as required in this dataset Select Values tab and then select multiple value fields of interest

Step 3: Creating Charts

For a chart:

1. Select data table in pivot table 2- Open Analyze Tab 3- Click on Chart options

We used different types of plot to represent data such as revenue, Product Category and Sales Distribution.

Step 4: Dashboard Structure

Creating the final dashboard: Users will insert new sheet for their report to maintain organization and visual consistency

Apply formatting according to specific needs or the user’s preference

Refresh Automate to see live performance update with a few clicks in pivot table and chart functionalities.

A collaborative approach to business intelligence has been achieved by making data accessible users while also allowing real-time interaction through various interactive tools within this excel framework.

**Shamima Sultana is Project Manager at ExcelDemy - where she does research on MS Excel and writes articles relating her work. She holds a BSc in Computer Science & Engineering and always tries to provide enriched content knowledge related to any subject with her innovative solutions