Unlock Your KPI Selection Skills with ChatGPT

Table of Contents

1. Introduction
2. Understanding Chat GPT
3. Analyzing a Real Data Set with Chat GPT
4. KPIs Derived from the Data Set
   • Total Sales by Category
   • Sales KPIs
   • Number of Orders
   • Shipping API
   • Average Shipping Time
5. Comparing with Tableau Dashboard
6. Shipping Analysis with Chat GPT
   • Average Shipping Time
   • Shipping Mode Analysis
7. Customer Analysis with Chat GPT
   • Customer Segmentation
   • Customer Retention Rate
   • Customer Account
8. Adding Additional Data Sets
9. Visualizing Insights with Different Chart Types
10. Organizing KPIs on the Dashboard
    • Executive Page Overview
    • Order Details Tab
11. Conclusion

Analyzing Real Data Sets with Chat GPT

In this article, we will Delve into the capabilities of Chat GPT—a new AI technology that assists in data analytics. We will explore how Chat GPT can be utilized to analyze a real data set, specifically the Sample Superstore data set. By sharing this data set with Chat GPT, we will assess its effectiveness in deriving key performance indicators (KPIs) for Tableau's Pulse feature.

Introduction

Tableau's Pulse feature is a powerful tool for data analytics, and understanding how Chat GPT can contribute to its usage is crucial. By leveraging Chat GPT's analytical capabilities, we can determine how well it can identify essential KPIs from the given data set.

Understanding Chat GPT

Before diving into the analysis, let's establish a clear understanding of Chat GPT. Chat GPT is an AI technology designed to assist users in deriving Meaningful insights from data sets. By utilizing natural language processing and machine learning algorithms, Chat GPT can interpret and analyze data, providing valuable KPIs and suggestions.

Analyzing a Real Data Set with Chat GPT

To assess Chat GPT's effectiveness, we will utilize the Sample Superstore data set, a widely-known and practical data set for retail analytics. We will examine the correlation between the data set and the KPIs suggested by Chat GPT.

KPIs Derived from the Data Set

By sharing the Sample Superstore data set with Chat GPT, we can observe the KPIs it identifies. Some of the significant KPIs identified are as follows:

Total Sales by Category

Chat GPT suggests analyzing the total sales by category to understand the performance of different product categories. This data can help in decision-making regarding product decommissioning or production increase.

Sales KPIs

The Chat GPT analysis includes the determination of sales KPIs such as the number of orders and order-related metrics. These KPIs provide insights into the sales performance of the Superstore.

Shipping API and Average Shipping Time

Chat GPT suggests calculating the average shipping time and analyzing the different shipping modes used. This information helps in understanding the efficiency of the shipping process and identifying commonly used modes and associated costs.

Comparing with Tableau Dashboard

To validate Chat GPT's suggestions, we compare its identified KPIs with Tableau's official Sample Superstore dashboard. We observe that Chat GPT's suggestions Align with the official dashboard, including KPIs such as total sales, regional sales, and sales by category. This highlights the accuracy and reliability of Chat GPT's analysis.

Shipping Analysis with Chat GPT

Chat GPT not only provides KPIs related to sales but also offers insights into shipping-related data. It suggests analyzing the average shipping time and shipping mode analysis. By performing these analyses, businesses can identify areas of improvement in their shipping processes.

Customer Analysis with Chat GPT

Another valuable aspect of Chat GPT's analysis is the examination of customer-related data. It suggests customer segmentation Based on geographic distribution and presents the count of customers by region. A recommendation for calculating customer retention rates is made, which proves to be an insightful KPI for evaluating customer loyalty.

Adding Additional Data Sets

Chat GPT's capabilities can be enhanced by incorporating additional data sets. By adding related data sets, such as regional managers and their performance metrics, insights on regional performance, benchmarking, and strategy can be obtained.

Visualizing Insights with Different Chart Types

Chat GPT also provides guidance on visualizing insights using various chart types. It suggests using horizontal bar charts or treemaps to showcase sales by region. Additionally, it recommends line or area charts for displaying sales growth trends over time.

Organizing KPIs on the Dashboard

To ensure effective dashboard visualization, it is essential to categorize and organize the KPIs appropriately. Chat GPT offers insights on which KPIs should be included on the executive page or the order details tab, providing Clarity on the presentation of information.

Conclusion

In conclusion, Chat GPT proves to be a valuable tool in data analytics, providing accurate and useful insights from real data sets. By utilizing its suggestions, businesses can save time and make informed decisions. While subject matter expertise remains essential, Chat GPT's assistance complements human decision-making, ensuring productivity and accuracy in data analytics tasks. So don't shy away from utilizing AI technology like Chat GPT—let it assist You as you navigate the complexity of data analytics.