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Paying monthly just to get your data in one place? There’s a better way. Many analysts, marketers, and small teams struggle with expensive tools, limited access, or endless CSV downloads. If you’re tired of these issues and want more control without the high cost, you’re not alone.
In this guide, you’ll learn how to combine JavaScript-powered connectors, SQL, BigQuery’s free tier, and OWOX Data Marts to create a cost-free pipeline that connects marketing ad platforms like Facebook Ads, Twitter Ads, TikTok Ads, stores your data in BigQuery, transforms any BigQuery data stored with SQL logic, and delivers live dashboards in Google Sheets or Looker Studio. Full transparency, no vendor lock-in, zero subscription costs.
A modern analytics stack is a set of connected tools used to gather, store, and analyze marketing and business data in one place. It helps teams avoid silos, reduce manual work, and get faster answers to important questions. By combining data from various sources and turning it into usable insights, this process enables smarter, more effective decision-making.
Here are some key benefits:
You can build a complete analytics stack without relying on expensive SaaS tools. Google BigQuery offers a generous free tier, up to 10 GB of storage and 1 TB of query processing each month, which is often enough for analysts or growing teams.
Google Ads & Google Analytics (GA4) data can be imported directly into your Google BigQuery.
💡If you need help with the same, you can check our articles: How to Upload Google Ads BigQuery Raw Data in 2025 and Google Analytics 4 to BigQuery - A Step-by-Step Guide
With OWOX Data Marts (Community Edition), you can use the free, open-source connectors to pull in ad data and ad spend from non-Google Ad platforms like Facebook, TikTok, and LinkedIn, without writing code. The data lands in BigQuery, ready to be transformed with SQL Queries into clean, analysis-ready tables.
Reporting is flexible too; you can use Google Sheets or Looker Studio as data destinations to share insights with your team using the structured data already in BigQuery. And because the entire system is open and customizable, it works just as well for product and sales data as it does for marketing.
This isn’t a workaround; it’s a modern, scalable stack designed for transparency, speed, and cost-efficiency. Built for teams that want answers, not complexity.
To build your own modern analytics stack, without subscriptions or vendor lock-in, you need just a few key components. Think of it as a DIY system: pull in raw data with OWOX connectors, store and query it using BigQuery’s free tier, and model everything with SQL to create clean, business-ready reports.
Every analytics stack starts with raw data. This includes data from platforms like Facebook Ads, LinkedIn Ads, and other ad platforms. APIs and internal databases also feed into the system. These are the starting points for everything that follows.
When these sources remain separate, it’s hard to get a full picture. That’s why a modern stack brings all this data together. Having a unified foundation avoids duplicate reporting, fills data gaps, and makes it easier to analyze customer behavior across multiple touchpoints.
Once you know where your data is coming from, the next step is bringing it into your system. This process is called ingestion. Instead of relying on manual CSV exports or expensive SaaS tools, you can use open-source connectors from OWOX to automatically pull data into your warehouse. OWOX’s open-source ingestion layer is built in JavaScript, giving you flexible, code-controlled access to marketing and analytics APIs.
Modern stacks often use the ELT method to extract the data, load it into storage, and then transform it later. This allows you to ingest raw data in real time and handle large volumes quickly. It also gives you more flexibility in how and when you process that data.
After ingestion, your data needs a reliable home. Cloud-based storage systems like Google BigQuery are ideal for this. They’re easy to manage, scalable, and accessible from anywhere. BigQuery’s free tier even gives you 10 GB of storage and 1 TB of query processing each month, perfect for small teams or early-stage projects.
Storing your data centrally allows everyone on your team to work from the same source of truth. Whether you're analyzing past performance or building new reports, having everything in one place keeps things consistent and avoids version conflicts across tools.
Raw data isn’t very helpful until it’s cleaned and structured. Using SQL in OWOX Data Marts, you can turn unorganized records into meaningful tables, like ad spend by channel, daily conversions, or cost per lead. This is the transformation step in the ELT flow.
Good transformation also includes data quality checks. You’ll filter out bad entries, fix inconsistent formats, and ensure everything is complete. This step makes your metrics accurate, reusable, and ready for dashboards. It also allows for consistent reporting across clients, teams, or marketing channels.
Once your data is cleaned and modeled, it’s time to turn numbers into insights. Tools like Looker Studio or Google Sheets help you build visual dashboards, reports, and summaries using your transformed data. These tools are simple, flexible, and widely used by both technical and non-technical teams.
Visualization is where data becomes actionable. You can track trends, compare campaigns, and identify what’s working or not at a glance. When everyone can understand the numbers easily, better decisions follow. It’s not just about charts, it’s about seeing what matters, quickly and clearly.
Even a free stack needs visibility and control. This final layer ensures your analytics setup runs reliably and securely as it scales. With OWOX, you can log every pipeline run, trace errors, and manage credentials inside your own environment, without exposing data to external systems.
Governance also means monitoring performance, validating data quality, and staying compliant with privacy rules. As your reporting expands, a strong governance layer keeps your stack trustworthy, so teams can act on data with confidence.
Paying monthly just to get your data in one place? There’s a better way. With BigQuery’s free tier, JavaScript-powered connectors, and the open-source OWOX Community Edition, you can build a complete analytics stack without expensive SaaS tools or CSV chaos. Here’s how to do it:
To run OWOX Data Marts locally, you need Node.js and the OWOX CLI. With this setup, you can launch a local server and use the Community Edition seamlessly.
Start by installing the latest LTS version of Node.js from nodejs.org, preferably with nvm or nvm-windows to avoid permission issues. After Node.js is ready, install the OWOX CLI globally and start the server with owox serve.
For full setup details or troubleshooting, refer to the official documentation.
Step 2: Enable BigQuery (Free Tier)
To get started, log into the Google Cloud Console, create a new project, and enable BigQuery. If you’re on the free tier, you’ll get 10 GB of storage and 1 TB of query processing each month, more than enough for solo analysts or small teams exploring automated reporting.
With BigQuery ready, the next step is to define how your data flows in and how it’s modeled for reporting. OWOX Data Marts uses two types of definitions: Connector Definitions for data ingestion and SQL Definitions for data transformation. Together, they turn raw platform data into structured, analysis-ready outputs.
Connector Definitions (Ingest Data into BigQuery):
SQL Definitions (Transform Data into Reports):
By combining connector and SQL definitions, you build a full data pipeline: ad platforms feed data into BigQuery, and SQL definitions turn that data into the metrics your team needs in Sheets or dashboards.
Check out the official docs to walk through each step in detail.
Destinations are the interfaces or applications where business users access the results of their Data Marts.
To set up a new destination, go to the Destinations page and click + New Destination. From the Destination Type dropdown, select the storage type you need:
Once selected, fill out the configuration fields required for that destination type (e.g., JSON key for Sheets, Deployment URL for Looker Studio). When finished, click Save to apply the configuration or Cancel to discard changes.
To connect your Data Mart to a Destination, open the Data Mart and go to the Destinations tab. All configured destinations, whether Google Sheets or Looker Studio, will be listed there.
For Google Sheets
You can connect your marts to Google Sheets to make pivot tables, charts, or shared reports.
For Looker Studio
You can also deliver marts to Looker Studio for interactive dashboards.
OWOX Data Marts supports two types of triggers, Connector Trigger and Report Trigger, to keep both your data ingestion and reporting layers fully automated.
Connector Run
Connector triggers are used to refresh data ingestion from ad platforms into BigQuery. Once set up, they ensure your warehouse always contains the latest campaign data.
Report Run
Report triggers automate SQL definitions after ingestion, transforming raw data into structured reports and pushing them to destinations like Google Sheets or Looker Studio.
Choosing between free tools and SaaS platforms depends on your goals, budget, and control needs. Before we walk through building your free stack, it’s worth seeing how this approach compares to traditional SaaS tools.
A self-hosted stack built with BigQuery’s free tier and OWOX’s open-source tools allows you to run analytics at almost zero cost. BigQuery gives you 10 GB of storage and 1 TB of monthly query processing for free, which is enough for many small teams or solo analysts. There are no extra charges for adding users or connecting new data sources within this setup.
In contrast, SaaS tools like Supermetrics and Funnel use subscription models that charge you per data source, per user, or based on data volume. As your reporting needs grow, so do your bills. For agencies or multi-brand teams, these costs can add up quickly and become hard to justify.
With open-source tools like OWOX, you have full control over your pipeline, from the way data is pulled to how it’s transformed and visualized. You can write your own SQL, adjust logic to fit business needs, and modify dashboards to meet client-specific reporting formats.
On the other hand, SaaS platforms offer plug-and-play convenience. Tools like Supermetrics offer ready-made connectors and templates that are quick to set up, but give you limited control to make changes. If flexibility is a priority, open tools give you more freedom, but if ease is key, SaaS may feel more comfortable.
Setting up a self-hosted stack with OWOX and BigQuery involves some technical knowledge. You’ll need to deploy scripts, write SQL for data modeling, and manage things like API limits or data freshness. This works best for BI engineers or analysts comfortable with databases and data flows.
SaaS platforms are built to be low-code or no-code. They offer guided onboarding, visual interfaces, and automation that make setup quick and beginner-friendly. For non-technical marketers or smaller teams without a developer, this makes SaaS tools easier to adopt, though at the cost of some control and customization.
Using open-source tools means everything stays within your infrastructure. You control where data is stored, how long it’s kept, and who has access. This setup supports better compliance, full audit trails, and tighter access policies, which are important for teams handling sensitive or regulated data.
In SaaS platforms, your data is routed through the vendor’s servers. They handle encryption, monitoring, and basic compliance features, but the data lives on their infrastructure. While this reduces setup work, it limits your visibility and may expose you to risks if their security practices don’t align with your internal policies.
Open tools like OWOX and BigQuery let you add new clients or projects without worrying about extra licenses. Whether you're building dashboards for one brand or ten, your only cost is tied to data volume or queries, not users or accounts.
But SaaS tools usually charge based on seats, users, or the number of connected accounts. For agencies or consultants managing multiple clients, this can make scaling expensive. Each new dashboard, data source, or user might require a separate fee, making it harder to maintain a predictable budget as your workload increases.
OWOX and other open-source tools offer connectors built by the community. These are flexible and free to modify, letting you adapt the setup to your exact needs.
Vendor-managed integrations in SaaS tools are professionally supported and easier to get started with. You don’t have to worry about maintenance, but you're limited by what the vendor provides. If a platform isn’t supported or custom logic is needed, you may have to wait for updates or rely on workarounds.
Comparison Table:
Managing ad data doesn’t have to mean high costs or rigid SaaS tools. With OWOX Data Marts (Community Edition), you can:
Check out the open-source library on GitHub and take full control of your data.
