Maximizing Insights: The 6 Best ChatGPT Techniques for Data Analysis

Over the past few months, there has been a rise in the number of artificial intelligence tools being released. One such powerful tool is ChatGPT, an advanced LLM capable of understanding and holding human-like text conversations.

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Though ChatGPT has been proven to generate conversational text, it has been a valuable asset for people across various industries. For data analysts, ChatGPT can be used to enhance their analytical capabilities and handle complex data challenges. Let’s look at some ways data analysts can use ChatGPT to be more productive in their day-to-day work.

1. Refine Ideas About a Task

Data analysts can leverage the capabilities of ChatGPT to refine and brainstorm about a task or case study. Since ChatGPT can generate conversational text, you can engage it and explore various perspectives by asking questions.

Suppose you want to write a script to automate a business process. You can ask ChatGPT for ideas on how to get started. All you have to do is ask it for a prompt via the chat and wait for its response. You can ask further questions or alternative viewpoints from the response.

Case Study: I have a business problem. I want to create a dashboard in Excel to segment and track the behavior of my customer. I currently run a coffee shop, and a few make orders via my e-commerce website.

What kind of information should I collect from my customers? What key performance indicators should I measure? Which tool and type of visualization should I use? Also, what kind of cohort analysis, and what will you recommend I incorporate for my user segmentation?

2. Fixing Bugs and Troubleshooting

You encounter bugs in your code, formula, or script during your day-to-day work as a data analyst. A conversational encounter with ChatGPT can provide debugging strategies, a fresh perspective, or even code solutions to the bugs.

ChatGPT can explain why your code threw the issue in the first place if you provide a prompt and the error message.

My prompt: I want this DAX formula to return a value based on the selected date on my filter. Year and month considered. However, the formula below returned an error.

`Customer Espresso and Cappuccino=

CALCULATE(

           SUM(‘Sales Data’[Amount]), ,

           KEEPFILTERS(‘Sales Data’[Product Type] =”Espresso” and ‘Sales Data’[Product Type] =”Cappuccino”)`

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3. To Interpret Data and Explain Complex Code

4. To Write, Edit and Generate Codes, Formula, and Syntax

In the same way that ChatGPT may be used to interpret complex coding. You can request that it create the code or syntax for you.

Case Study: You have a Python if statement with a for Loop . Your current code only checks if the length of myList is precisely 3 and loops through it if the statement is true. Otherwise, it executes the else statement and outputs each item in myList2. However, you would like to modify it to print all items in either list with exactly four letters instead.

My prompt: can you modify this Python code to print all items in either list with exactly four letters instead:

`myList = [‘Python’, ‘MUO’, ‘Hello’]

myList2 = [“Fish”, “Gold”, “Bag”]

if len(myList) == 3:

   for items in myList:

       print(items)

else:

   for items2 in myList2:

       print(items2)`

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5. Learning New Skills

We have an article on how you can add a static date and time in Google Sheets . You can use ChatGPT to learn more about this topic or how to do something similar in a different application. For example, how to add a static date and time in Tableau.

By writing a prompt, you can learn about new features and skills, or how to use a specific function in your favorite analytical tool.

6. Document Your Codes

Codes that have comments are easier to read. But you can admit that everyone finds the process boring and monotonous. ChatGPT can perform this task effortlessly and with great accuracy and efficiency.

Ask it a question, and it will provide you with fully commented code you can copy and paste in response.

My Prompt: Can you add comments to this SQL code:

`SELECT

 e.employee_id AS “Employee #”

 , e.first_name || ‘ ‘ || e.last_name AS “Name”

 , e.email AS “Email”

 , e.phone_number AS “Phone”

 , TO_CHAR(e.hire_date, ‘MM/DD/YYYY’) AS “Hire Date”

 , TO_CHAR(e.salary, ‘L99G999D99’, ‘NLS_NUMERIC_CHARACTERS = ‘’.,’’ NLS_CURRENCY = ‘’

‘’) AS “Salary”

 , e.commission_pct AS “Comission %”

 , ‘works as ‘ || j.job_title || ‘ in ‘ || d.department_name || ‘ department (manager: ‘

   || dm.first_name || ‘ ‘ || dm.last_name || ‘) and immediate supervisor: ‘ || m.first_name || ‘ ‘ || m.last_name AS “Current Job”

 , TO_CHAR(j.min_salary, ‘L99G999D99’, ‘NLS_NUMERIC_CHARACTERS = ‘’.,’’ NLS_CURRENCY = ‘’

‘’) || ‘ - ‘ ||

     TO_CHAR(j.max_salary, ‘L99G999D99’, ‘NLS_NUMERIC_CHARACTERS = ‘’.,’’ NLS_CURRENCY = ‘’

‘’) AS “Current Salary”

 , l.street_address || ‘, ‘ || l.postal_code || ‘, ‘ || l.city || ‘, ‘ || l.state_province || ‘, ‘

   || c.country_name || ‘ (‘ || r.region_name || ‘)’ AS “Location”

 , jh.job_id AS “History Job ID”

 , ‘worked from ‘ || TO_CHAR(jh.start_date, ‘MM/DD/YYYY’) || ‘ to ‘ || TO_CHAR(jh.end_date, ‘MM/DD/YYYY’) ||

   ‘ as ‘ || jj.job_title || ‘ in ‘ || dd.department_name || ‘ department’ AS “History Job Title”

FROM employees e

– to get title of current job_id

 JOIN jobs j

   ON e.job_id = j.job_id

– to get name of current manager_id

 LEFT JOIN employees m

   ON e.manager_id = m.employee_id

– to get name of current department_id

 LEFT JOIN departments d

   ON d.department_id = e.department_id

– to get name of manager of current department

– (not equal to current manager and can be equal to the employee itself)

 LEFT JOIN employees dm

   ON d.manager_id = dm.employee_id

– to get name of location

 LEFT JOIN locations l

   ON d.location_id = l.location_id

 LEFT JOIN countries c

   ON l.country_id = c.country_id

 LEFT JOIN regions r

   ON c.region_id = r.region_id

– to get job history of employee

 LEFT JOIN job_history jh

   ON e.employee_id = jh.employee_id

– to get title of job history job_id

 LEFT JOIN jobs jj

   ON jj.job_id = jh.job_id

– to get namee of department from job history

 LEFT JOIN departments dd

   ON dd.department_id = jh.department_id

ORDER BY e.employee_id;`

Data Analysts Can Use ChatGPT in Their Work

Powerful AI solutions like ChatGPT boost everyone’s productivity, even data analysts. Using ChatGPT’s natural language processing capabilities and asking the right prompt, data analysts can quickly and accurately get ideas and insight into their tasks.

However, while ChatGPT can be a collaborator in your work, it’s vital to critically evaluate and test its feedback. So explore this fantastic technology, integrate it into your workflow, and let me know your thoughts.

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Though ChatGPT has been proven to generate conversational text, it has been a valuable asset for people across various industries. For data analysts, ChatGPT can be used to enhance their analytical capabilities and handle complex data challenges. Let’s look at some ways data analysts can use ChatGPT to be more productive in their day-to-day work.