Export Google Maps Leads to Power BI, BigQuery and Tableau Without Rebuilding Your List

You can move Google Maps leads into Power BI, BigQuery, or Tableau from one export. Run the Maps search, export CSV, XLSX, or JSON, and load that file with the native import in each tool. GoLeads Pro has no native connector for these tools, so the file itself is the handoff, and a clean file keeps the dashboard honest.

I learned this on an agency report that looked fine everywhere except the numbers. Duplicate rows sat in the sheet, two date shapes shared one column, and phone numbers had turned into plain numbers in Excel. The dashboard showed what the file said. The file was wrong.

Rebuilding the list from the export, cleaning it once, and loading it again fixed the report. Say you search dentists in Miami and you need that list inside a dashboard your team already opens. You will see which file suits each tool, how I load it, and what I check before I share the report.

Pick the file for the tool that will read it

Format choice sounds small, and it shapes the whole load. CSV loads fast and works everywhere. XLSX carries a ready made sheet with headers in place. JSON suits a database table where a script reads the records.

The sheet work that feeds these loads sits at Export Google Business Profile Data to Excel and Google Sheets. That post covers the cell by cell work.

Run the export like the dashboard will judge it

Dashboards punish a sloppy source file fast. One service, one place, one export, every time. I scan the Maps results before I export, and I fix a mixed search term at that point. A dashboard built on a mixed list shows pretty charts about the wrong businesses.

1. Run one Maps search for one service in one city or neighbourhood.
2. Start the GoLeads Pro extension from the Maps results page and finish the extraction.
3. Check the row count against what Maps showed before you export anything.
4. Export CSV for BigQuery and Tableau work, or XLSX for a Power BI sheet load.
5. Save the file with the search term and date in the name.
6. Open the file once and check phone, rating, and review count columns before loading.

A dated copy of the raw export stays untouched in my folder. Dashboard loads often need a rework after the first chart shows a fault, and a raw copy lets me reload without running the search again.

Power BI: set the types before the table lands

Power BI loads a CSV or XLSX file through Get Data. I choose Text or CSV for a CSV file, or Excel Workbook for an XLSX file, then I open Power Query Editor before I load. Setting types in Power Query beats fixing them after the load. Phone goes to text, postcode goes to text, rating goes to a decimal number, review count goes to a whole number.

Once the types read right, I close and apply, and the table lands in the model. Simple visuals come first: a count of leads by category, a count by city, and a table of the highest rated businesses. A map visual needs latitude and longitude, and a plain Maps export may not carry those fields.

Refresh here means a fresh file load. No live pull runs from Maps in this workflow. I save each new export with a new date in the name, load it as the new source, and check the row count before I publish. A count that jumps or drops sharply stops the publish.

BigQuery: let it guess, then fix phone by hand

BigQuery loads a CSV or JSON file into a table you create. I create a dataset, create a table inside it, and choose Upload. The file format gets set to CSV or JSON to match the export, and I let BigQuery auto detect the schema on the first load. Then I review every field type before I run a query. Auto detection still guesses wrong on phone numbers, so I set phone to STRING by hand.

After the load I run a count query and a duplicate check on phone and business name. A count that matches the export row count tells me the load kept every row. A duplicate check tells me whether the source file itself had repeats. Duplicates get fixed in the sheet before a reload, rather than hidden by queries.

BigQuery suits a team that already stores data there and wants Maps leads beside other tables. For a one off list you will call from once and discard, the sheet workflow is faster and easier to hand to a caller.

Tableau reads phone as a number unless you stop it

Tableau connects to a CSV through Text File or to an XLSX through Microsoft Excel. I connect, check that Tableau read the header row as field names, and set phone to a string field before I build any view. A phone column read as a number drops leading zeros the same way Excel does.

My first views stay plain: a category bar chart, a city count, and a detail table with name, phone, website, and rating. The detail table matters most, because the person using the report will call from the table. Sorting the table by rating and review count puts the strongest listings at the top of the view. Sorting helps the reader. It is a reading aid.

Tableau refresh works the same way as Power BI refresh in this workflow. You load a new export file when the list changes. No live feed runs from Maps into Tableau through GoLeads Pro. A dated file load, checked before publish, is the honest refresh cycle.

The other destinations people search for, answered straight

Searchers ask about other destinations by name, and the answer is the same file workflow with a different load step. Looker Studio takes a CSV upload or a Google Sheet, so I load the CSV into Sheets first and connect the sheet. PostgreSQL takes a CSV through a COPY command or a database client import, with phone set to text in the table definition. Redshift, Qlik, and Monday each accept a file import or a sheet import, and the export file is the bridge in each case.

I claim no native GoLeads Pro connector for any of these tools. The vendor list I work from covers exports in CSV, XLSX, and JSON, mapped for HubSpot, Salesforce, Apollo, Pipedrive, and Zoho, with Zapier and Make on higher tiers. That list says nothing about Power BI, BigQuery, Tableau, Redshift, Qlik, Monday, Looker, or PostgreSQL, so I treat every one of those as a file load. If a future release adds a direct link, this workflow still works.

Background on what a lead extractor does before any export sits at What Is a Lead Extractor, and the general export guide sits at Export Google My Business Data. If you are weighing free tools first, Free Lead Scrapers for Google Maps sets out what free options cover.

Worked example: Miami dentists, from search to shared report

Say you search dentists in Miami for a team report. You tighten the term until the set reads as dentists only, run the extension, and export CSV. Phone, rating, and review count get a quick read in the sheet, duplicates get cut on a phone sort, and a dated raw copy goes into the folder.

Power BI takes the file through Get Data, then Text or CSV, with Power Query setting phone to text before the load. Category counts and city counts come first, then a detail table sorted by rating. The report row count gets matched against the export row count, and a few phone numbers get read back to check leading zeros.

Only then does the report go to the team, with the source file name, search term, and export date in the report notes. That note lets someone trace a strange number back to its run a week later.

A pre-share checklist that takes two minutes

• Row count matches the export.
• Phone sample keeps leading zeros.
• Duplicates on phone and name are gone.
• Rating is a number, review count a whole number.
• Blank emails stay blank.
• Source, term, and date sit in the report notes.

I run that list before any report goes to a team.

Mistakes that make a dashboard lie

Loading without setting types comes first. Phone turns into a number, leading zeros drop, and every call from the detail table starts with a wrong number. The fix sits in Power Query, in the BigQuery schema review, or in the Tableau connect screen.

Publishing without a row count check comes next. A load that cut off the last rows of a file looks complete on screen. The fix is a count match between dashboard and export, every time, before publish.

Hiding duplicates with a filter comes after that. A filter that drops repeats from view leaves them in the table. The fix is a dedupe in the sheet, then a reload, so the table itself is clean.

Planning around a live feed that does not exist is the last one. Teams have built refresh schedules on an assumed link, then found stale data on launch day. The fix is a dated file load in the plan, with a named person running the fresh export.

A dashboard nobody can trace back to its file fails as a report.

When a dashboard is overkill

A dashboard earns its place when a team reads the same list for weeks, splits it by city or category, and acts on the counts. A list you call once and discard does not need one. The sheet workflow covers that job faster.

Small lists fall in the same bucket: thirty rows need a sorted sheet with a filter, and the team can start calling in minutes.

Cost stays plain here. GoLeads Pro reports a free tier of 50 leads a day, up to 300 leads in total, with no credit card required, and that figure is vendor reported. A 300 row file is enough to test a dashboard layout before you commit to a larger list.

Frequently asked questions

Can GoLeads Pro send leads straight into Power BI?

No native link of that kind is part of the product as described here. You export CSV or XLSX from GoLeads Pro, then load the file into Power BI through Get Data. Set the phone column to text in Power Query before you load, check the row count, and publish. A fresh export file is the refresh step when the list changes.

Can I load Google Maps leads into BigQuery?

Yes, through a file load. Export CSV or JSON, create a table in BigQuery, and upload the file. Set phone to STRING by hand, because auto detection may read it as a number and drop a leading zero. Run a count query after the load and compare it with the export row count.

Does Tableau connect directly to Google Maps through GoLeads Pro?

No direct link is claimed here. You export CSV or XLSX, connect Tableau to the file, and set phone to a string field at connect time. Build your category and city views from that file, and reload a fresh export when the list changes. The file load is the whole bridge, and it works without any extra tool in between.

Which export format should I pick for a dashboard?

Pick CSV for BigQuery, Tableau, and database loads, because it loads fast and every tool reads it. For a Power BI load, XLSX fits when you want a ready made sheet with headers in place. JSON fits a BigQuery load when a script will read structured records. Match the format to the tool that reads the file, and keep a CSV copy for a quick human check.

How much can I export for free before I build a dashboard?

GoLeads Pro reports a free tier of 50 leads a day, up to 300 leads in total, with no credit card required, and that figure is vendor reported. Exports cover CSV, XLSX, and JSON, mapped for HubSpot, Salesforce, Apollo, Pipedrive, and Zoho, per the vendor. Zapier and Make sit on higher tiers.

How do I refresh a dashboard when the list changes?

I run the search again, export a fresh file, and save it with the new date in the name. The fresh file loads as the new source, and I check the row count against the export plus a few phone numbers for leading zeros. Publishing waits until those checks pass, so the team never sees a report built on a half loaded file.

Can I combine leads from two cities in one dashboard?

Yes, if you add a city column before you load the files. I load each city file with the same headers, tag each row with its city, and stack the rows into one table. I run the duplicate check on phone numbers after stacking, because a business near a city edge can appear in both files. The city filter then splits the views cleanly.

What do I do when the dashboard count and the export count differ?

I stop and find the gap before I share anything. Filters get checked first, since a filter can hide rows, then duplicate removal steps, then whether the load cut off the last rows of the file. The raw export copy loads again, counts get compared again, and a dashboard I cannot reconcile stays a draft until the counts match.

Run a search, export the file, and load it into the dashboard your team already opens. Get the GoLeads Pro extension and start with the free tier.