Cloud Storage
Azure Data Lake
Connect your AI to Azure Data Lake
Data engineers, analytics teams, and finance operations land exports, extracts, and curated datasets in Azure Data Lake Storage, but the file that answers a question sits deep in a folder hierarchy that only the people who built the pipelines can navigate. AI can find and read the right file on demand, but only if it stays inside the containers, folders, and access controls each role is allowed.
Why it matters
Capabilities that matter most for Azure Data Lake
01
Fill the lake from any connector
Copy lists from almost any Popdock connector into Azure Data Lake, split by day, month or year on a date field, as CSV or Parquet files.
02
Retire old ERPs into the lake
The Data Lake Exporter moves Dynamics GP, NAV, SL and SQL Server history, attachments included, into the lake so it outlives the system it came from.
03
Query the lake as lists
Files in the lake become lists you can filter, join, chart and hand to AI tools, scoped to the containers and folders each role is allowed.
Use cases
Example AI Use Cases for Azure Data Lake
scenario
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The answer to a simple question, like which customers are on hold or who manages a territory, often sits in a CSV extract in Azure Data Lake. Getting it means knowing which container and folder holds the latest file, downloading it and filtering it in a spreadsheet, so most people wait for someone on the data team to do it for them.
What popdock provides
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Ask Claude, ChatGPT or Microsoft Copilot a question in plain words and PopdockAI reads the Azure Data Lake files your admin has set up as lists, such as customer, vendor and salesperson extracts, and returns the matching rows as an answer. The AI filters, sorts and limits the results only through the fields your admin exposes, so nobody needs to browse storage, write a query or know where a file lives.
Business outcome
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Anyone can get an answer from the data lake in a chat, without a download or a request to the data team.
scenario
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Finance teams often need a slice of a data lake extract, such as customers over their credit limit or vendors in one class, in a workbook they can share. Pulling the raw file, trimming it to the right rows and columns and tidying it for Excel takes time and is easy to get wrong when the file has hundreds of columns.
What popdock provides
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Ask Claude, ChatGPT or Microsoft Copilot for the rows you need, for example customers with a balance over a set amount, and PopdockAI reads the Azure Data Lake list and returns a real Excel file with a set file name and worksheet. Your admin decides which columns the file contains and which filters the AI may apply, so every workbook comes out in the same shape with only the fields that matter.
Business outcome
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A clean, filtered workbook from the data lake in one request, ready to share without manual cleanup.
scenario
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Opening Azure Data Lake to AI is a hard sell when the storage holds customer, vendor and finance extracts side by side. Sharing storage keys or broad access with every user and AI client risks exposing files and fields people should never see, and leaves no record of what was read.
What popdock provides
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IT turns only the chosen Azure Data Lake files and folders into lists, then decides which of them each user, team and AI client can use, down to the fields returned and fixed filters the AI cannot remove. Claude, ChatGPT and Microsoft Copilot reach the data through governed MCP tools in PopdockAI, the storage credentials stay in Popdock, and every call is logged with the user, client, request and response.
Business outcome
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AI can use the data lake within limits IT sets and can audit, with no storage keys handed out.
scenario
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Pipelines often drop a new file into an Azure Data Lake folder every day or every run. Answering a question across all of them means downloading each file and stitching them together before you can even start, and one missed file skews the result.
What popdock provides
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Your admin sets up an Azure Data Lake folder as a single list, so its files are read together as one dataset. Ask Claude, ChatGPT or Microsoft Copilot a question and PopdockAI reads across the whole folder, applying the filters, sort order and record limits your admin allows, and returns the answer or a file. As new files land in the folder they are included without anyone changing the setup.
Business outcome
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Questions about a folder of files are answered across every file at once, with nothing to download or combine.
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