Getting Started
The Platform
Data Integrations
Privacy & Security
How it works
AdLibertas functions as your private end-to-end data cloud: we do the heavy lifting of managing your data so you can focus your efforts on more valuable activities.
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.
Connecting in 3 steps
Knowledge Base
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.
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 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.
The AdLibertas Approach to Big Data - AdLibertas
AdLibertas
Step 3. End-User Reporting & Access
Rich, interactive reporting and custom dashboarding
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.
Our Customers - AdLibertas
AdLibertas
Interactive, custom reporting & prediction models
Your organization can compare audience datasets across performance metrics and custom events. See the article on how predicted LTVs work here.
Direct SQL Access & Custom Processing
For customers who want direct access to the data, we offer direct SQL access via Amazon Athena, or end-points to access and download reports. Additionally, customers can spin up their own computing clusters to run advanced or custom models against their users or custom datasets.