---
title: "Getting Started"
id: "1750"
type: "page"
slug: "getting-started"
published_at: "2026-09-20T21:16:33+00:00"
modified_at: "2026-09-21T01:36:28+00:00"
url: "https://xedant.com/agents/analytics/docs/getting-started"
markdown_url: "https://xedant.com/agents/analytics/docs/getting-started.md"
excerpt: "Analytics Agent is a web platform for interactive visual analytics: fast dashboards and reports from…"
---

# Getting Started

[https://xedant.com/agents/analytics/docs/getting-started.md](https://xedant.com/agents/analytics/docs/getting-started.md)

Analytics Agent is a web platform for interactive visual analytics: fast dashboards and reports from your data, with deep drill-down, AI right in the interface and built-in Python. It resembles Grafana, but the focus is not on monitoring — it is on real analysis: here you don’t just watch metrics, you dig deeper — filter, cross-check, calculate, ask the AI.

## Who it is for

Analytics Agent is made for analysts and teams who find “look-only” dashboards not enough. The product was created by an analyst with more than 25 years of experience in data and visualization — it shows in the details: from the block grid to server-side histogram calculations.

## System requirements

Any Linux host with Docker: the app deploys as a single container, all data in the `/data` volume, and Python for Jupyter Notebooks is already in the image. Step-by-step instructions are in the [Installation](/agents/analytics/install)
 section.

## First sign-in

The login and password are set by the `ANALYTICS_ADMIN_LOGIN` and `ANALYTICS_ADMIN_PASSWORD` environment variables (the variable holds the SHA-256 hash of the password). Without them, signing in is impossible. Sessions work through JWT tokens with a 90-day lifetime.

## The interface

- **Documents** — the report tree with breadcrumbs for nested folders, search across all documents as you type, recent history;
- **Templates** — a library of 257 ready-made analysis templates: forecasts, segments, scoring and an analytics course (details in [Analysis Templates](/agents/analytics/docs/templates) );
- **Data Sources** — SQLite, PostgreSQL, ClickHouse;
- **Lakehouse** — a file browser for your data: Parquet, SQLite, Markdown;
- **Alerts** — rules, contact points, histories and silences;
- at the bottom of the sidebar — active agent chats and the prompts queue; settings (font, sign-out) live in the gear menu.

The interface language (English or Russian) is chosen by the brand at install time; the theme — dark or light — switches in the interface. Sound notifications about new agent messages can be turned off with one button in the header.

## Your first report

- create a document with the “New document” button;
- add blocks: a chart, a table, a metric — and drag them around the grid;
- connect a data source in the “Data Sources” section;
- write a SQL query in the block configuration — or ask the AI to do all of it for you in plain language.

A report can be made interactive: put filters and what-if fields into the header, enable click-to-drill, assemble tabs for different readers and export the finished result to PDF. Details in the [Reports & Documents](/agents/analytics/docs/reports)
 section.

## What’s next

How documents work is described in [Reports & Documents](/agents/analytics/docs/reports)
, what they are made of — in [Block Types](/agents/analytics/docs/blocks)
 and [Charts](/agents/analytics/docs/charts)
. Connecting databases — in [Data Sources](/agents/analytics/docs/data-sources)
, how the AI works — in [the agent in the report](/agents/analytics/docs/agent)
, ready-made solutions — in [Analysis Templates](/agents/analytics/docs/templates)
.

[← Back to the documentation index](/agents/analytics/docs)