Akkio Docs
  • Akkio Documentation
    • Akkio FAQ
  • Account and Settings
    • Team Settings
    • Organization Settings
    • Account Settings
    • Role Based Access Control
  • Demo Models
    • Demo Models
      • Lead Scoring
      • Retail Sales Forecasting
      • Predict Credit Card Fraud
      • Identify Customer Churn
  • Setting up Integrations
    • Connecting Data
    • Airtable (Beta)
    • Google Ads (Beta)
    • Google Analytics 4 (Beta)
    • Google BigQuery
    • Google BigQuery (Service Account)
    • Google Sheets
    • HubSpot (Beta)
    • MariaDB (Beta)
    • MongoDB (Beta)
    • MySQL (Beta)
    • PostgreSQL (Beta)
    • Redshift (Beta)
    • Salesforce
    • Akkio Data Chat for Slack
    • Snowflake (Username / Password) (Beta)
    • Zapier
  • Prepare your Data
    • Prepare
      • Chat Data Prep
      • Clean
      • Merge & Fuzzy Merge
      • Table View
      • Pivot View
      • Deploying Chat Data Prep
  • Explore
    • Chat Explore
    • Chart Types
  • Building a Model
    • Predict
      • Insights Report - Classification
      • Insights Report - Regression
    • Forecasting
      • Insights Report - Forecasting
    • Model Types
  • Deploying a Model
    • Deploy
      • Google BigQuery
      • Google Sheets
      • HubSpot (Beta)
      • PostgreSQL (Beta)
      • Salesforce
      • Snowflake (Beta)
      • Web App
      • Zapier
  • REPORTING AND SHARING
    • Reports
    • Dashboards
  • REST API
    • API Introduction
      • Quickstart
    • API Options
      • cURL Commands
      • Python Library
      • Node.js Library
    • API FAQ
  • Rest API (v2)
    • Documentation
Powered by GitBook
On this page

Was this helpful?

  1. Setting up Integrations

Connecting Data

Connect data to begin training a model

PreviousIdentify Customer ChurnNextAirtable (Beta)

Last updated 11 months ago

Was this helpful?

The first step to creating a project in Akkio is to connect data, as data is the fuel for any machine learning model. Akkio is a tabular AI tool, which means you’ll want historical data in a tabular format, such as a CSV, Excel file, Snowflake dataset, or dataset. Other options include , , Hubspot, and .

In machine learning, quality, and quantity are important, so high-quality, large datasets are preferred. “Quality” means having few missing values, properly formatted data, and data indicative of the problem you’re trying to solve. There’s no minimum dataset size for connecting to Akkio, but ideally, your dataset is at least a couple hundred rows, preferably thousands (or millions) of rows.

Crucially, your dataset must be indicative of the problem at hand. For Example, you’ll need a historical customer dataset with a churn column to predict churn.

Salesforce
Google Sheets
Google BigQuery
PostgreSQL