Adverity for Fivetran users

This guide is designed to help users familiar with Fivetran to start using Adverity.

Introduction

This guide explains how concepts and processes in Fivetran are comparable to the features available in Adverity. Our aim is to make it as simple as possible for you to migrate from Fivetran to Adverity.

To start your migration from Fivetran to Adverity, take a look at the guide on our website: Adverity or Fivetran?

Structure

Adverity’s workspaces give you optimum control and flexibility when organizing the workspace structure within your organization. In Adverity, the workspaces in your organization are set up in a tree structure, with one root workspace and multiple child workspaces. These come with the following benefits:

• Settings and elements within the platform can be used across multiple workspaces in your organization.

• Data Mapping in Adverity helps you to harmonize data that you collect from different data sources throughout your organization.

For more information about workspaces in Adverity, see our guides to Creating workspaces and Workspace settings.

The table below compares the structures used in Fivetran and Adverity. The diagram shows a visual comparison of the workspace structure in Fivetran and Adverity.

Fivetran structure	Adverity structure
Create separate accounts (equivalent to Adverity workspaces)	Hierarchical tree structure with workspaces on different levels
Users can be granted access to one or more accounts	Configure and use datastreams, authorizations, transformations and Data Mapping across workspaces
Create user groups to manage access rights	Use data and other content from child workspaces in your current workspace

Collecting data

In Adverity, you create authorizations that allow you to collect data from your chosen data sources. You collect this data using datastreams.

For more information about collecting data in Adverity, see our guide to Creating a datastream.

The table below summarizes the differences between Fivetran and Adverity, and the advanced data collection settings that Adverity offers. The diagram shows a visual comparison of the data collection process in Fivetran and Adverity.

Fivetran	Adverity
Each connector automatically fetches default reports for all selected accounts	Offers complete customization and control over what fields are fetched from the data source and allows you to schedule fetches to keep your data up-to-date
Create custom reports to fetch additional data	Creates a single datastream to collect the selected fields
One-off historical data sync in the initial fetch, then additional historical fetches can be performed for an additional cost	Allows you to choose how much historical data to collect, when to schedule these data fetches, and how often to collect data in future. Some data sources have limits on historical data fetches.
Authorize each data source per connector	Authorize Adverity to access your data source using your credentials, or ask someone else (with or without an Adverity account) to authorize access for you
Auto-scheduling available based on attribution window	Schedule fully customizable data fetches - choose what data to collect and how often to collect this data

Managing data

In Adverity, you apply Data Mapping to the data you collect in order to harmonize the information you fetch from different data sources. This means you can easily compare and visualize similar data, such as costs and clicks, from different data sources.

For more information about Data Mapping, see our guide to Applying Data Mapping to a datastream.

Once you have collected your data, you can use Adverity’s transformations to transform the data to meet your needs. Adverity offers standard transformations and custom scripts, which let you completely customize the data you have fetched.

For more information about transformations, see our guides to Using standard transformations and Using custom script transformations.

The table below summarizes Fivetran’s custom fields and the ways you can manage data in Adverity. The diagram shows how Data Mapping can help you create a single source of truth for all your data in Adverity.

Fivetran	Adverity
Data transformations are based on SQL	Complete flexibility in how you add, remove and change fields in your data
Data is only transformed in your destination - only your raw data is available in Fivetran	Standard transformations - a user-friendly interface to help you transform your data
No option to customize data mapping	Custom script transformations - a wider range of transformation options using Python
	Data Mapping harmonizes data from all your data sources

Sending data to other tools

After collecting your data and making sure it meets your needs using Data Mapping and transformations, use Adverity’s destinations to send your data to other tools for further analysis.

Connect a destination to Adverity to send data to a wide range of external tools and databases. When you want to load data into your destinations, you simply choose the data you want to send and load it into your choice of external tool or database. For more information, see our guide to Loading data into destinations.

The table below summarizes the options available in Fivetran and Adverity when sending data to other tools.

Fivetran	Adverity
Assign a destination to one or more connectors	Assign one or more destinations to each datastream to automatically load data into these destinations when you fetch new data
Fivetran sends all data from all reports to your destination	Proactively choose the data you want to load into an external destination
Schedule data transfers from Fivetran to your destination	Transfer data every time you fetch - some destinations, e.g. PowerBI and Tableau, automatically pull data from Adverity so you always have the latest data in your BI tool
Creates a relational data model and transfers data in this format to your destination	Creates a report-based structure per datastream and transfers data in this format to your destination