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Imagine asking, “What is our cost of acquisition per channel?” Or, “Are high-usage customers more likely to stay on paid plans?” And just literally getting the answer. Let’s build a data analyst agent.

Creating a data analyst agent is surprisingly simple. We’ll start by connecting our database. I’m going to use BigQuery, but you can use Snowflake, Salesforce, Airtable, whatever you consider a database. Then I’ll authenticate it, and that’s it.

I can already ask my agent questions like, “What is our MRR growth over the last three months?” And our Gumloop agent will start exploring and analyzing our database. AI is exceptional at this type of work. And come back to us with an answer. This is a data analyst agent, and it’s ready to go.

Now, it’s not the most efficient data analyst agent. If I look at the tool calls between my question and its answer, the agent is spending a lot of time and tokens and effort figuring out our database. It’s listing all the tables, the schemas. It’s going to do that in every conversation because agents have no memory. We can fix this by creating a skill, a reusable set of instructions so the agent knows what it’s looking at, simply by asking, “Write me a skill about our BigQuery setup.” It’ll explore the tables, relationships, and write itself a guidebook on what it understood, which it can reuse in the next question or any agent can reuse.

Here’s that same question again. “What is our MRR growth over the last three months?” Notice how much more efficient it is. It started by reading its skill and instantly knew where to go.

Two more tips to getting the most out of your data analyst agent. First, give it more tools. Let’s give it Google Sheets so it can spit analysis out to a sheet or compare a forecast that lives in a spreadsheet to actual data in our database. Same with email, so it can automate reports for you with something like, “Every Friday at 9 a.m., send me a report of our revenue over the last week broken down per channel.”

Final tip, bring your agent into Slack so everyone can finally start asking the questions they’ve always wanted to. In fact, not ask questions, but get answers.

Data Analyst Agent

Connect your database to a Gumloop agent so anyone on your team can ask data questions and get answers instantly.

Apps
BigQueryBigQuery
Google SheetsGoogle Sheets
GmailGmail
1

Create an agent and connect your database

Connect the database where your data lives.
BigQueryBigQuery
SnowflakeSnowflake
AirtableAirtable
SalesforceSalesforce
Create an agent
2

Start asking your agent questions

Just by connecting your tools, you can already use your agent. Ask it anything about your data and it will explore your database and come back with an answer.
What is our MRR over the last 3 months?
3

Create a skill

Your agent will be drastically more performant if it writes itself a skill with instructions on how your database is structured.
Write a skill on how our BigQuery is structured
Creating a skill in Gumloop
4

Add more tools

Your agent can do so much more than just answer questions. Add in other tools your team relies on.
Google SheetsSheets
GmailGmail
AsanaAsana
LinearLinear
5

Bring your agent to Slack

Give everyone on your team the power of getting answers instantly by bringing your agent into Slack.