In recent months, the number of AI tools released has been increasing. ChatGPT is a powerful tool, an advanced large language model (LLM) that can understand and engage in human-like text conversations.
While ChatGPT has proven capable of generating conversational text, it can greatly benefit people across various industries. For data analysts, ChatGPT can enhance analytical capabilities and tackle complex data challenges. Let’s explore several ways data analysts can use ChatGPT to improve their work efficiency in their daily tasks.
1. Refining Ideas for a Task
Data analysts can leverage ChatGPT’s capabilities to improve and brainstorm tasks or case studies. Since ChatGPT can generate conversational text, you can use it to explore different perspectives by asking questions.
Suppose you want to write a script for automating a business process. You can ask ChatGPT how to get started. All you need to do is feed it a prompt in the chat and wait for a response. You can ask further questions or seek additional viewpoints based on the answer.
Case Study:I have a business question. I want to create a dashboard in Excel to segment and track customer behavior. I currently run a coffee shop and have several customers placing orders through my e-commerce website.
What information should I collect from my customers? What key performance indicators should I measure? What tools and types of visualizations should I use? Additionally, what kind of cohort analysis would you suggest I include in user segmentation?
2. Fixing Errors and Troubleshooting
As a data analyst, you will encounter errors in your code, formulas, or scripts in your daily work. Engaging in conversations with ChatGPT can provide debugging strategies, new perspectives, and even solutions for fixing erroneous code.
If you provide prompts and error messages, ChatGPT can explain why your code is throwing issues.
My prompt:I want this DAX formula to return a value based on the date selected on my filter. Considering year and month. However, the formula below returns an error.
3. Interpreting Data and Explaining Complex Code
When trying to understand a long and complex piece of code, ChatGPT has proven to be helpful. In such cases, copy and paste the code you are trying to understand and say, “Explain this code” to request a response.
4. Writing, Editing, and Generating Code, Formulas, and Syntax
ChatGPT can also be used to explain complex coding. You can request it to create code or syntax for you.
Case Study:You have a Python if statement with a for loop. The current code only checks if the length of myList is exactly 3, and if true, it loops through it. Otherwise, it executes the else statement and outputs each item in myList2. However, you want to modify it to print outputs of all items in either list that have exactly four letters.
My prompt:Can you modify this Python code to print outputs of all items in either list that have exactly four letters:
5. Learning New Skills
Previously, an article was published on how to add static dates and times in Google Sheets. You can use ChatGPT to learn more about this topic or find out how to do similar things in different applications. For instance, how to add static dates and times in Tableau.
By crafting prompts, you can learn new features and skills or understand how to use specific functions in your commonly used analytical tools.
6. Writing Documentation for Code
Commented code is easier to read. But you have to admit, everyone finds this process boring and tedious. ChatGPT can effortlessly perform this task with high accuracy and efficiency.
Ask it a question, and it will provide you with commented code that you can copy and paste.
My prompt: Can you add comments to this SQL code:
Data Analysts Can Use ChatGPT in Their Work
Powerful AI solutions like ChatGPT can enhance productivity for everyone, including data analysts. By utilizing ChatGPT’s natural language processing capabilities and asking the right prompts, data analysts can quickly and accurately gain insights and ideas about their tasks.
However, while ChatGPT can be an assistant in your work, critically evaluating and testing its feedback is crucial. So explore this amazing technology and integrate it into your workflow.(Translated by Bugatti)
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