Azure Blob Storage

Azure Blob Storage is Microsoft's cloud object storage service. It stores unstructured data — files like CSVs, JSONs, Parquets, and Excel sheets — that you can connect to Coupler.io and sync into your analytics tools, data warehouse, or spreadsheets.

Why connect to Coupler.io?

• Centralize cloud file data — Pull files from Azure containers directly into Google Sheets, BigQuery, Looker Studio, or Claude without manual downloads
• Support multiple formats — Work with CSV, JSONL, Parquet, Excel, and unstructured data in a single data flow
• Automate file syncs — Schedule regular refreshes so your dashboards and reports always reflect the latest blobs
• Combine with other sources — Use Join or Append transformations to merge Azure file data with CRM, ad platform, or database records

Prerequisites

You'll need:

• An active Azure subscription with access to Blob Storage
• Storage account name (find it in the Azure Portal under Storage Accounts)
• Container name where your files are stored
• Storage account key (primary or secondary, available under Access keys in the Azure Portal)
• Files in a supported format: CSV, JSONL, Parquet, Excel, or unstructured text

Quick start

Start with a single CSV or Parquet file in your container. Once you confirm the sync works, expand to multiple files using glob patterns (e.g., data/*.csv).

How to connect

1

Log in to Coupler.io and create a new data flow. Choose Azure Blob Storage as your source.

2

Enter your Azure Blob Storage account name. This is the name of your storage account in Azure (e.g., mystorageaccount). Do NOT include the full domain — just the account name.

3

Provide your storage account key. In the Azure Portal, go to your storage account and select Access keys under Settings. Copy the primary key (or secondary key) and paste it into the Coupler.io form.

4

Enter the container name where your files are stored (e.g., raw-data, imports, or exports).

5

Specify the file path or glob pattern. For a single file, enter the exact path (e.g., sales.csv). For multiple files, use a glob pattern (e.g., data/*.csv to match all CSVs in the data folder, or reports/**/*.parquet to match Parquets in nested folders).

6

Choose your file format from the dropdown: CSV, JSONL, Parquet, Excel, or Unstructured. This tells Coupler.io how to parse and structure the data.

7

Set a start date (optional). If you want to sync only files modified after a certain date, use the date picker. Leave blank to sync all files matching your path pattern.

8

Choose your destination — Google Sheets, BigQuery, Looker Studio, Excel, or an AI destination like Claude or ChatGPT. Select the target sheet, table, or dataset where you want the data to land.

9

Run the data flow manually by clicking the play button. Wait for the flow to complete successfully before scheduling.

Supported file formats

Format	Best for	Notes
CSV	Structured tabular data	Most common; handles headers and quoted fields
JSONL	Nested or semi-structured data	One JSON object per line; flexible schema
Parquet	Large datasets, analytics	Compressed, columnar format; preserves data types
Excel	Multi-sheet workbooks	Supports .xlsx and .xls; syncs one sheet per flow
Unstructured	Logs, text, raw content	Raw file content as plain text