AI agent for data analysis and reporting
An AI agent for data analysis is software that does an analyst's desk work: it pulls, cleans and analyses your data and reports what it shows. A Monmo agent writes the SQL, checks the rows, keeps a dashboard current and delivers the weekly report from its own computer, on a schedule. It asks before changing a shared record. What to measure and what to decide stay with you.
Updated 2026-11-13 · Free to start. Paid plans from $15 a month.
The job description, line by line
Each line is a duty that appears in typical job descriptions for this role. Beside it is how the agent handles that line and how far it goes on its own.
- Does itResearch, reading, drafting and building. Nothing leaves your business.
- Does it, asks firstThe last step sends, posts, pays or changes a record, so it shows you a card first.
- Prepares it, you decideThe line needs your judgement. The agent brings the facts and a recommendation.
- Stays with youCalls, meetings in person, signatures and relationships.
| # | In the job description | How the agent does it | How far it goes |
|---|---|---|---|
| 01 | Pull data from databases and other sources using SQL queries. | Writes the SQL from your question and your table definitions, then runs it through the database connection you choose, such as BigQuery or Snowflake, or in the tool's own console in its browser. Each query is saved beside its result in Google Sheets. | Does it |
| 02 | Clean, validate and combine data, checking for duplicates, gaps and odd values. | Works on a copy of your Google Sheet or Excel export unless you say otherwise. It removes duplicate rows, standardises dates and currencies, joins sources on a shared key, and lists every change and unresolved row in a notes tab. | Does it |
| 03 | Analyse data to find trends, patterns and outliers. | Breaks each metric down by week, segment and channel with the data tools on its computer, checks whether a change is larger than the usual week-to-week swing, and marks each outlier in Google Sheets with the rows behind it. | Does it |
| 04 | Build and maintain dashboards and charts that track key metrics. | Builds the dashboard as a summary tab of charts in Google Sheets, one per metric with its target line, and refreshes it before each Monday. Changes to a dashboard your team already shares, for example in Tableau, wait for your approval. | Does it |
| 05 | Produce recurring weekly and monthly reports for managers and other teams. | Every Monday at 8:00 it rebuilds the KPI report in Google Slides from fresh data, with last week and the target beside each figure. You get it first. Emailing it to managers or other teams asks first. | Does it |
| 06 | Answer one-off business questions with focused analysis. | Ask in plain words, by message or voice note, for example why refunds rose in March. It pulls the rows, tests two or three explanations and answers in a one-page Google Doc with the query, a chart and what remains uncertain. | Does it |
| 07 | Automate the routine steps of preparing data and producing regular reports. | Turns a report you have checked once into a routine: the same queries, checks and layout run on the schedule you agree, such as the first working day of each month. It tells you when a source has changed or a step fails. | Does it |
| 08 | Write plain-language summaries of what the numbers show and what they do not. | Opens each report with five lines a non-analyst can read: what changed, by how much, the likely cause, and what the data cannot tell you, such as a sample too small to trust. Every figure names the Google Sheets tab it came from. | Does it |
| 09 | Fix data quality problems at the source with the teams that own the data. | Lists the bad records with a reason for each, such as 43 Salesforce accounts with no region, and drafts a Slack message to the team that owns them. Sending the message and correcting any record wait for your approval. | Does it, asks first |
| 10 | Agree what to measure, metric definitions and priorities with stakeholders. | Drafts a metric dictionary in Google Docs: each measure, its formula, its source table, and where two teams count it differently. You and the stakeholders settle the definitions and the priorities. The agent then applies them in every report. | Prepares it, you decide |
| 11 | Present findings to decision-makers and advise on what to do next. | Prepares the deck in Google Slides: the finding as each slide's title, the evidence beneath it, and two or three options with their trade-offs in the speaker notes. You present it, and the recommendation is yours to make. | Prepares it, you decide |
| 12 | Follow data protection and security rules when collecting, storing and sharing data. | Uses only the apps you allow, asks before a file is shared from Google Drive, and can mask names and emails in an export. It lists the personal data each report contains, so you can decide which rules apply and who may see what. | Prepares it, you decide |
9 of 12 lines handled by the agent, some after your approval
Where the duties come from. The twelve lines are the duties that appear most often in public job descriptions for data analysts and reporting analysts, reworded, and checked against the O*NET task list for business intelligence analysts. Checked against O*NET OnLine: 15-2051.01 Business Intelligence Analysts
A week with your AI data analysis agent
Refreshes yesterday's numbers, runs the duplicate and gap checks, and tells you in three lines if a metric moved more than usual.
Rebuilds the weekly KPI report and the dashboard tab, with last week and the target beside each figure.
Pulls the rows, tests the likely explanations and answers in one page with the query and a chart.
Lists the records that failed the quality checks and drafts a note to each team that owns them, ready for your approval.
Writes up the week's questions and answers in plain language, and notes any metric that two teams define differently.
Builds the monthly report in Google Slides and the draft deck for your leadership meeting.
What you give it on day one
- Read access to your data: the database, the Google Sheets or the exports you report from
- The reports you send today, so it can match the layout and reconcile the numbers
- Your metric definitions: how you count an active customer, revenue and churn
- Who receives which report, and on which day
- The rules: which data is sensitive, and where files may be shared
What stays with you
- Deciding what to measure and how each metric is defined.
- Presenting to leadership and making the recommendation. It builds the deck and the options.
- Which data protection rules apply, and who may see what.
- Changes to source systems. It lists the bad records; the team that owns them makes or approves the fix.
Hire one in three steps
- 01
Write the role
Create an agent, name it, and describe the job as you would to a new analyst: which numbers matter, who reads the reports, and what a wrong figure would cost. Paste your job description if you have one.
- 02
Give it access
Connect Google Sheets and your database with your own accounts, and choose that this agent may use them. It reads first, to learn your tables, your definitions and last quarter's reports.
- 03
Set the first routine
Ask it to rebuild last week's report by 9:00 tomorrow and compare its figures with yours. Correct what differs, then agree the Monday routine. It keeps your corrections for every report after that.
First things to ask
- Pull orders by region and week for the last 13 weeks from the orders table. Show me the SQL and put the result in a sheet.
- Why did refunds rise in March? Check by product, channel and customer type, and tell me how sure you are.
- Every Monday at 8:00, rebuild the KPI report with last week and the target beside each number.
- List the customer records that fail our checks and draft a note to the sales team. Ask me before sending.
Watch it work
A sample replay with example data, sped up. Pause it, scrub through it, or take the mouse yourself.
On screen
Google Drive
Google Sheets
Google Docs
Salesforce
Google Slides
Pick a job. Watch it get done.
Your team. Connected to everything.
FY27 launch budget+FY27 launch budget
Expected case · prepared by Ren · sample data
Japan launch adds $474k from March.
Sea freight, six-week lead time.
Marketing peaks in launch month.
Sample replays with fictional data, sped up. Pause one, scrub through it, or take the mouse yourself.
Questions people ask
What is an AI agent for data analysis?
An AI agent for data analysis is software that does an analyst's desk work on its own: it writes queries, cleans data, builds charts and writes the report. A Monmo agent does this on its own computer with the data sources you connect, on a schedule or when you ask, and asks before it changes a shared file or record.
Can an AI agent replace a data analyst?
It takes over the pulling, cleaning, charting and recurring reports, which fill much of an analyst's week. It does not decide what to measure, settle a definition between two teams, or stand in front of leadership with a recommendation. Teams use it so that a person spends the time on the questions and the decisions instead of the exports.
Can it write and run SQL?
Yes. Describe what you need in plain words and it writes the SQL from your table definitions, runs it through the database connection you set up and returns the result with the query attached. Reading needs no approval. A statement that would change data, such as an update or a delete, is shown on a card first.
How do I know the numbers are right?
Every figure comes with its working: the query, the source table or tab, and the row counts before and after cleaning. The agent reconciles its totals against a figure you already trust and says so when they differ. It can still misread a definition, so check a new report as you would a new analyst's. Your corrections carry forward.
Which data tools does it work with?
Google Sheets, Excel and CSV files are the most common. Databases and BI tools such as BigQuery, Snowflake and Tableau are in the app directory. The agent uses the account you connect and has the permissions that account has. Where a connection does not cover a step, it can use the tool in its own browser.
Is it safe to give an AI agent access to company data?
You choose which apps the agent may use, and it sees only what the connected account can see. It asks before it shares a file, emails a report or changes a record, and you can watch its screen while it works. Which data may be used at all remains your decision, under your own data protection rules.