The Scenario
You've been asked to put together a market snapshot of data analyst job postings for a workforce intelligence report. The brief says: pull 500 LinkedIn job postings matching "data analyst" and get them into an Excel workbook for analysis. Your company has a Bright Data account with access to pre-made datasets. You open the workbook. It's blank.
The task got handed to you on Tuesday because you're "good with data." The report is due Thursday.
The bad version:
- Log into Bright Data's marketplace, find the LinkedIn Jobs dataset, figure out what filter parameters it accepts, trigger a snapshot with the keyword "data analyst", wait for it to process, download the output file, realize it's a 40MB JSON with nested arrays you weren't expecting, write a Python script to flatten the relevant fields, run it, fix the encoding error on row 312, paste the output into the workbook.
- Realize the columns you wanted — title, company, location, date posted, job URL — are scattered across different nesting levels in the JSON and your script missed two of them.
- It's now Wednesday evening.
You were supposed to be analyzing this data, not parsing it. Someone somewhere decided your time was worth less than the thirty minutes it took to learn how this dataset is structured.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that reads your Excel workbook and talks to Bright Data's marketplace datasets directly. You describe the dataset, the filter, and the destination columns — SheetXAI triggers the snapshot, waits for it, parses the result, and writes the structured fields into your workbook.
List the available Bright Data marketplace datasets, trigger a filtered snapshot for LinkedIn job postings with the keyword "data analyst", and import the results — job title into column A, company name into column B, location into column C, date posted into column D, and job URL into column E — for up to 500 records starting in row 2
What You Get
- Up to 500 rows of LinkedIn job posting data written into columns A through E
- Each row is one job posting: title, company, location, date posted, and direct URL
- If the dataset returns fewer than 500 records for the filter, all available records are written and the actual row count is noted in a header comment
- Any field that is missing or null for a given record is written as blank rather than causing the row to shift
What If the Data Is Not Quite Ready
I want to filter to a specific location as well as keyword
Trigger a Bright Data LinkedIn Jobs dataset snapshot filtered to the keyword "data analyst" and location "New York", import the results into columns A through E with title, company, location, date posted, and job URL — up to 500 records
I need Amazon product data instead of job postings
Use a Bright Data pre-made dataset to extract Amazon product listings for the search term "wireless headphones", import the results with product title into column A, price into column B, rating into column C, review count into column D, and ASIN into column E — up to 500 rows starting in row 2
The workbook already has some data and I need to append, not overwrite
Trigger a Bright Data LinkedIn Jobs snapshot with keyword "data analyst", then append the new results starting below the last populated row in column A — do not overwrite existing data
Filter, deduplicate by company, sort by date, and import in one pass
Trigger a Bright Data LinkedIn Jobs snapshot filtered to keyword "data analyst" and location "Remote", import results into columns A through E, deduplicate rows by company name keeping the most recently posted job, and sort the output by date posted descending
One prompt replaces the download-flatten-import cycle entirely.
Try It
Open any blank Excel workbook and get the 7-day free trial of SheetXAI — ask it to trigger a Bright Data marketplace dataset snapshot and import the structured results into your columns. You can also explore how to crawl competitor domains for content analysis or review the full Bright Data integration overview.