Get to know Adverity

Get to know Adverity#

Before diving into the hands-on guides, take a few minutes to understand how Adverity works. This guide gives you a high-level overview of the platform, how data flows through it, and what you can achieve.

What can I achieve with Adverity?#

Your marketing data is likely spread across many different sources, such as Facebook Ads, Google Ads, analytics platforms, and more. Without a way to bring it all together, comparing performance across channels can be difficult.

Adverity solves this by letting you collect data from all your sources, transform and harmonize it so metrics are comparable, and then analyze or export it wherever you need. Whether you want to build dashboards, feed data into a BI tool, or simply have a single source of truth, Adverity provides the pipeline to get you there.

How is Adverity organized?#

Everything in Adverity lives within workspaces. A workspace is a container for your datastreams, authorizations, destinations, and other resources. You’ll need at least one workspace before you can start collecting data. To create your first workspace, see Creating and deleting workspaces.

Most organizations use multiple workspaces to separate data by team, client, or region. For help choosing the right structure, see Best practices for workspace structure.

Platform areas at a glance#

The Adverity platform is divided into three main areas: Connect Data, Manage Data, and Use Data. Each area contains multiple pages that you can access from the navigation menu on the left side of the screen.

Connect Data: Configure datastreams, manage authorizations, and monitor performance in Activity. For operational insights, see Introduction to the Activity page and Using the Performance Manager.
Manage Data: Create and reuse transformations, maintain the Data Dictionary, manage monitors, and manage mapping and value tables.
Use Data: Query data using Data Conversations, manage destinations, and work in Explore and Present.

How data flows through Adverity#

Here’s the journey your data takes from source to insight:

Authorize access

Enable secure connection to your data sources and destinations. Allow Adverity access by creating or selecting an authorization (reusable across datastreams).

If you want to learn more about authorizations, see Authorizations overview.

Collect data with a datastream

Create your collection pipeline and first data extracts. Configure a connector and authorization, choose fields, and run a fetch. Data is stored in local storage as data extract files.

If you want to learn how to create a datastream, see Creating a datastream.

If you want to configure fetch types and scheduling, see Manual, Smart, and Custom fetches.

Monitor data quality (Optional)

Catch issues early, right after collection. Use monitors to detect anomalies before processing and loading.

If you want to learn how to configure data quality checks, see Introduction to the Data Quality page.

Transform data (Optional)

Prepare data for consistent mapping and downstream use. Apply transformations to clean, enrich, and standardize values before loading.

If you want to learn how to enrich and clean data, see Transformations overview.

Map source fields to target fields

Ensure only standardized target fields flow to analytics and destinations. Use Data Mapping so similar concepts across sources align (for example, “spend” and “cost”). Only mapped target fields can be loaded and analyzed.

If you want to learn how to harmonize fields, see Harmonizing data.

Store data in a warehouse for Adverity analytics

Load data into a warehouse that powers Data Conversations as well as Explore and Present. Use a warehouse managed by Adverity or connect your own external warehouse.

If you want to learn how to load data into a warehouse, see Load data into a warehouse.

Load to additional external destinations (Optional)

Make standardized data available in external tools. Send data to BI tools, files, or databases (for example, Looker Studio, Tableau, S3, BigQuery).

If you want to learn about sending data to external tools, see Destinations overview.

Get data insights with AI (Optional)

Get insights using natural language on data loaded to a warehouse.

If you want to get access to your data with natural language, see Data Conversations.

Analyze and present (Optional)

Explore answers interactively and share results with stakeholders. Build widgets in Explore and assemble dashboards in Present using mapped data from ADS or your warehouse.

If you want to create analyses, see Explore overview.

If you want to build dashboards, see Present overview.

What’s next?#

Now that you understand how Adverity works, you’re ready to start building your first pipeline. Continue to the next guide: Creating a datastream.

Or, if you’d like to explore specific topics in more depth:

Set up authorizations: Learn how to create and manage authorizations. See Creating and viewing authorizations.
Create and edit target fields: Define standardized dimensions and metrics used in mapping and analysis. See Creating and editing target fields.
Use Default Data Mapping: Use and adjust connector-provided defaults to accelerate mapping. See Default Data Mapping.
Get insights with Data Conversations: Query your data using natural language. See Using Data Conversations.
Manage users: Configure user settings and permissions. See Managing users.
Performance optimization: Monitor task health and identify bottlenecks. See Using the Performance Manager.