# How it works

<div align="left"><img src="https://www.adlibertas.com/wp-content/uploads/2022/09/InputsToOutputs-v2.png" alt="more details about the platform"></div>

### **Step 1. API Data Collection**

We have 100+ APIs that are scheduled to batch-fetch your data from all in-app service providers. We don’t require an SDK for integration, and most data can be collected by simply connecting credentials.

{% embed url="<https://adlibertas.gitbook.io/product-docs/data-integrations/integrate-in-3-steps>" %}

### **Step 2. Data Pipeline: Processing & Storage**

**Scheduled Data Import & ETL**

Our scheduled, overlapping data import schedules ensures the latest data available is accessible while back-fetching ensures any later-posted data is added to keep data access timely and correct.

We’ve pre-built the ETL & processing algorithms so there’s no need for you to wrestle with scripting your own.

**Fully managed data lake**

For every AdLibertas customer, we spin up a single-tenant AWS account to house and store your data. We’ve architected your data to be stored as ORC files in S3 buckets. This maximizes long-term cost-efficiency and maintains accessibility and security for all clients. There’s no maintenance or overhead needed.

&#x20;                                                 ![](/files/xVFutmLHpDXuSPSNSYK4)

&#x20;                                                     **Building your own Data Pipeline: Best Practices**

For app developers that want to architect, build and maintain their own data architecture, AdLibertas Head of Architecture, Allen Eubank, [shares our experiences](https://www.adlibertas.com/mobile-data-architecture-and-data-pipeline/) in building a scalable, reliable data pipeline.

**Fast, parallel-distributed query processing**

For processing the many petabytes of information generated by our clients, we adopted *Trino* a fast, highly parallel, and distributed query engine that is built from the ground up for efficient, low latency analytics at scale.&#x20;

&#x20;                                                     <img src="/files/73N9T8QDixUTh6Y27YwM" alt="" data-size="original">

&#x20;                               [<mark style="color:blue;">Read how and why</mark>](https://trino.io/users.html#adlibertas) AdLibertas uses *Trino* to enable their customers.

{% embed url="<https://www.adlibertas.com/the-adlibertas-approach-to-big-data>" %}

### **Step 3. End-User Reporting & Access**

**Rich, interactive reporting and custom dashboarding**

![Dashboard and reporting](/files/i4xjb2KKKpr3hgKaqHVn) ![BI & Analytics](https://www.adlibertas.com/wp-content/uploads/2022/01/customDash.png)

**Self-service no-SQL exploration**

Our analytics give all users in your organization the ability to build custom-defined user datasets, defined by user-events, actions, and/or user characteristics. There’s no need for complicated SQL-joins or custom Tableau reports, anyone can simply drag and drop user-audiences. This gives your organization complete control and flexibility in refining their data-sets to find the important users and actions in your app.

![](https://www.adlibertas.com/wp-content/uploads/2022/02/mediator-gif.gif)

{% embed url="<https://www.adlibertas.com/our-customers>" %}

**Interactive, custom reporting & prediction models**

Your organization can compare audience datasets across performance metrics and custom events. See the [<mark style="color:blue;">article on how predicted LTVs work here</mark>](https://docs.adlibertas.com/the-platform/user-level-audience-reporting/forecasting) and see how our proprietary machine learning predictions can help you get fast, accurate campaign predictions here

![](https://www.adlibertas.com/wp-content/uploads/2021/10/buildpltv.png)

**Direct SQL Access & Custom Processing**

For customers who want direct access to the data, we offer direct [<mark style="color:blue;">SQL access via Amazon Athena</mark>](https://www.adlibertas.com/supporting-amazon-athena-access/), or end-points to [<mark style="color:blue;">access and download reports.</mark>](https://docs.adlibertas.com/the-platform/business-analytics) Additionally, customers can spin up their own computing clusters to run advanced or custom models against their users or custom datasets.

### Reporting Workflow

<figure><img src="/files/m4ctH7e0NCweshHEv2xK" alt=""><figcaption></figcaption></figure>

[**User-level Audience Reporting**](/the-platform/user-level-audience-reporting.md) allows you to create hyper-specific reports on user-level characteristics and behavior. From here, we store these reports in the [analytics](/the-platform/business-analytics/analytics-layout.md) system -- accessible via the "[Explore Data button](https://docs.adlibertas.com/the-platform/business-analytics/understanding-the-explore-data-button)"-- so you can add them to a [custom dashboard](https://docs.adlibertas.com/the-platform/custom-dashboards) or compare them against other user-level reports.

[**Consolidated Revenue Reporting** ](/the-platform/consolidated-revenue-reporting.md)allows you to view your earnings in [pre-built charts](https://docs.adlibertas.com/the-platform/consolidated-revenue-reporting#rich-reporting-built-for-ad-supported-apps) or drill directly into [analytics](/the-platform/business-analytics/analytics-layout.md) to create your own reports.

[<br>](https://www.adlibertas.com/knowledge-base/adlibertas-audience-reporting/)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.adlibertas.com/the-platform/how-it-works.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
