The Fastest Way to Add BI to Your Product

Want to integrate Business Intelligence (BI) into your product quickly and effectively? Here's how you can do it in just days, not months:

• Why BI Matters: BI transforms raw data into actionable insights, helping teams track KPIs, spot trends, and act in real time. Embedding BI eliminates manual data wrangling and provides instant, trustworthy insights directly within your product.

• The Problem Without BI: Teams waste time on outdated reports and scattered data, missing opportunities to predict trends or prevent customer churn.

• The Solution: Querio, an AI-driven analytics platform, simplifies BI integration with tools like natural language querying, real-time dashboards, and embedded analytics. It connects directly to your data warehouse (e.g., Snowflake, BigQuery, Postgres) without duplicating data, ensuring fast and secure insights.

• Steps to Get Started:

  1. Identify the BI features your users need (e.g., dashboards, predictive analytics).

  2. Ensure your data warehouse is ready (clean schema, clear naming conventions, granular access controls).

  3. Connect Querio to your data warehouse for live, real-time data access.

  4. Build dashboards with Querio’s natural language interface - no SQL required.

  5. Embed these dashboards into your product for seamless user experience.

Key Benefits:

• Save time: Set up BI in days instead of months.

• Empower users: Enable self-service analytics with easy-to-use tools.

• Ensure security: Querio uses read-only access and is SOC 2 Type II certified.

• Scale with ease: Manage growing data needs without overhauling your system.

Querio makes BI integration fast, secure, and user-friendly, helping you deliver insights where they matter most - within your product.

5-Step Process to Integrate BI into Your Product with Querio

Step 1: Review Your Product's BI Requirements and Data Setup

Determine Which BI Features You Need

Start by figuring out which BI (Business Intelligence) features will bring the most value to your users. For example, natural language querying lets users ask questions in plain English and get instant results like charts or tables - no need to mess with complex SQL queries. If your team relies heavily on performance metrics, embedded analytics can integrate dashboards right into your product's workflow. In fact, adding this feature can increase BI usage by as much as 500%.

Does your product need predictive analytics? This feature is great for forecasting trends or identifying issues like customer churn before they happen. AI-driven analytics can deliver insights up to 40% faster than traditional BI tools. And for advanced users who want more control, self-service exploration allows them to create custom views on the fly.

"BI tells you what, AI helps you understand why - and more importantly, what to do next."
– Michael Cargian, AI Evangelist, SingleStore

Once you’ve nailed down the features you need, the next step is to ensure your data setup can handle them.

Check Your Data Infrastructure

Your data warehouse or database needs to be up to the task of supporting the BI features you’ve chosen. For instance, Querio works seamlessly with platforms like Snowflake, BigQuery, and Postgres. Make sure your data is stored in one of these systems. Querio requires read-only access and automates the initial mapping process to identify your main data source - eliminating the headache of building complex ETL pipelines.

Before connecting, take time to clean up your data. Audit your schema and remove any unused tables or fields to keep things tidy. Use clear, human-readable column names (e.g., "Customer Name" instead of "CustID"). Organize your data by separating fact tables (like transactions or sales) from dimension tables (such as customer details or product categories). Also, standardize your data values - don’t mix formats like "Open", "open", and "opn" in the same column.

Finally, make sure your system supports granular access controls so users only see the data they’re allowed to access. While Querio is SOC 2 Type II certified, your data warehouse still needs to maintain solid security protocols on its end.

Step 2: Connect Querio to Your Data Warehouse

Live Connections: Snowflake, BigQuery, and Postgres

Querio integrates directly with your data warehouse, accessing your data in real time without ever copying or moving it. Whether your data resides in Snowflake, BigQuery, or Postgres, Querio simply reads it where it is. This ensures your data remains up-to-date and eliminates the hassle of syncing or duplicating storage. Here's how you can set up connections for each platform.

For Snowflake, start by creating a dedicated service account with a username and password or use a Personal Access Token (PAT) or Private Key. You'll need to provide your Account ID (formatted as org_name-account_name), along with details like Warehouse Name, Database, Schema, and Table. When connecting to BigQuery, Querio uses either service account keys or OAuth 2.0 for authentication. For Postgres, use a standard username-password combination, along with the host, port, and database name. These connection methods are designed to align seamlessly with your existing infrastructure, making it easy to embed BI into your product.

"What used to be a week-long process now takes minutes."
– Jennifer Leidich, Co-Founder & CEO, Mercury

Security is a top priority in every connection. Querio only requires read-only access, ensuring it cannot perform any data-modifying actions like CREATE or ALTER. Credentials, such as Snowflake passwords, are securely stored in AWS Secrets Manager and encrypted using AWS Key Management Service (KMS) with tenant-specific Customer Managed Keys. Querio also meets stringent security standards, including SOC 2 Type II certification, providing robust protection for your data.

To optimize your setup, use dedicated service accounts instead of high-privilege roles like ACCOUNTADMIN. Ensure the warehouse you connect to is active or can resume quickly to avoid delays. If your network has firewalls or specific policies, whitelist Querio's production IP ranges to ensure a smooth connection.

Connection Methods Compared

Here’s a quick breakdown of how Querio connects to each data warehouse:

Each option provides real-time access with minimal setup. The main differences lie in authentication methods and platform-specific security protocols. Once connected, Querio automatically maps your source data into its data model - no SQL required. With the connection in place, you're ready to start building and embedding dashboards.

Step 3: Build and Embed Dashboards with Querio

Create Dashboards for KPI Tracking

Creating dashboards in Querio is refreshingly straightforward, thanks to its natural language interface. Forget about needing SQL or coding skills - just type questions in plain English, like "What's our monthly recurring revenue by region?" Querio instantly generates accurate charts, ready to pin with a single click. What used to take weeks can now be done in minutes.

The drag-and-drop interface makes it easy to organize charts, tables, and metrics. You can monitor key performance indicators such as customer acquisition costs, churn rates, or sales pipeline velocity, all updated directly from your data warehouse. Querio's Centralized Context Layer ensures that joins and metrics are defined once, providing a single, reliable source of truth across all dashboards.

"I immediately started saving 7-10 hours a week!" – Guilia Acchioni Mena, Co-Founder, Zim

You can also schedule automatic dashboard deliveries - say, every Monday at 9:00 AM - keeping your team informed without manual effort. This self-service approach allows IT teams to focus on higher-level strategic tasks.

Once your dashboards are set up, the next step is embedding these insights for your users.

Embed Analytics for End-Users

After crafting insightful dashboards, you can seamlessly integrate them into your product to enhance user engagement. Embedding Querio dashboards ensures that analytics align perfectly with your product’s design system - using Headlines APIs and theme tokens, the dashboards match your colors, fonts, and styles. The result? Analytics that feel like a natural part of your product, not an external add-on.

End-users can dive into interactive exploration through features like interactive notebooks. They can ask follow-up questions, drill down into details, save their own queries, pin key insights, and access pre-built dashboards tailored to their specific roles. With granular security controls, users only see data relevant to their permissions, ensuring compliance with SOC 2 Type II standards. By embedding these analytics directly into your product, you empower users to make informed decisions right where they work, boosting both engagement and the value they perceive in your platform.

Step 4: Customize with Querio's Python Notebooks and Semantic Layer

AI Python Notebooks for Advanced Analysis

Sometimes, your team needs to dig deeper than what standard dashboards offer - whether it's analyzing forecasting models, examining cohort behavior, or running custom statistics. Querio's AI-powered notebooks make this process seamless. They let you run both SQL and Python queries without starting from scratch. All you have to do is ask your questions in plain English, and the AI takes care of the rest, pulling data directly from your live warehouse while maintaining the same governed context that powers your dashboards.

These notebooks go beyond simple queries. The AI actively supports your exploration, suggesting follow-up questions and helping you uncover deeper insights. Plus, since Querio automatically applies your business-specific terminology, the results are always aligned with your unique domain needs. This means your data team can focus on strategic initiatives instead of constantly fielding one-off requests, while product managers and analysts get the answers they need - fast.

Security remains a top priority, with the platform enforcing read-only data access to ensure that even advanced analysis doesn't compromise safety. You can save your queries, share notebooks across teams, and build a library of reusable templates, making it easy to scale your analysis as your product evolves.

The Semantic Layer: Your Single Source of Truth

Once you've enhanced your analysis with Python notebooks, the next step is ensuring consistency across your data, and that's where the semantic layer comes in.

Querio's semantic layer acts as the foundation for defining how data operates across your entire product. Your data team maps technical database columns to plain business terms, sets up table joins, and defines key metrics like "monthly recurring revenue" or "customer lifetime value." From then on, every dashboard, notebook, or embedded analytics view draws from this unified source of truth.

This means no more confusion from different teams calculating the same metric in different ways. For example, when someone asks, "What's our churn rate?" - whether in a dashboard or a notebook - they'll get the same answer every time. The context-aware engine ensures these business rules are applied consistently, whether it's a finance analyst creating a report or an end-user exploring embedded analytics.

Querio's AI simplifies the setup, automatically mapping database elements to everyday business language in just minutes. As your product and data structures grow, you only need to update definitions once in the semantic layer, and those changes instantly apply across all tools and reports.

Step 5: Monitor, Govern, and Scale BI Capabilities

Governance with Querio's Context Layer

Once your dashboards and notebooks are up and running, it's crucial to establish strict governance to prevent misinterpretation of metrics or unauthorized access to sensitive data. Querio's context layer makes this possible by implementing granular access control directly at the data level. Your data team can define exactly who sees what - whether that means limiting a sales team to their specific region’s data or restricting access to finance metrics based on roles.

With SOC 2 Type II compliance and read-only access, your data remains secure as your user base grows. Every prompt, output, and data retrieval is logged, creating a comprehensive audit trail. This traceability is invaluable for verifying compliance or troubleshooting unexpected insights. Additionally, Querio ensures your proprietary information stays private by never using customer data to train its AI models.

This robust security framework ensures that your BI capabilities are scalable and reliable as your business evolves.

Scaling BI Alongside Product Growth

As your product grows, so will your data needs. More users, larger datasets, and increasingly complex queries are inevitable. Querio’s architecture is designed to handle this growth seamlessly, without requiring you to overhaul your existing infrastructure. Since it operates directly on your live data warehouse - whether it’s Snowflake, BigQuery, or Postgres - you avoid the inefficiencies of duplicating data or managing separate analytics databases that can slow down performance.

To manage scaling costs, you can monitor token usage and set spending limits on complex queries. Before rolling out new features, validate them using synthetic data to ensure they’re production-ready. This approach allows you to expand your BI capabilities - whether that’s adding dashboards, notebooks, or embedded analytics - while maintaining the same governed context layer. This ensures consistent accuracy and security across all interactions as your data demands grow.

Conclusion

Key Takeaways

Bringing business intelligence (BI) into your product doesn’t have to be a lengthy or resource-heavy process. By connecting Querio directly to your live data warehouse - whether you use Snowflake, BigQuery, or Postgres - you can skip complicated ETL workflows and avoid duplicating data. Querio’s natural language interface allows your team to query data instantly, reducing IT data request backlogs by up to 80%, all while maintaining governance through its centralized context layer.

With features like embedded dashboards, AI Python notebooks, and a semantic layer, Querio equips both internal teams and end-users with advanced analytics - without the need to build everything from the ground up. Real-world examples show that when BI is integrated effectively, tasks that once took weeks or hours can now be completed in minutes. These time savings translate into measurable efficiency gains, paving the way for quicker deployment and immediate results.

The key to success is starting with a clear understanding of your BI needs, setting up a context layer early to ensure consistent metrics, and utilizing Querio’s robust security tools to scale confidently. With SOC 2 Type II compliance, granular access controls, and detailed audit trails, you can expand your BI capabilities while ensuring data accuracy and security.

Next Steps with Querio

Begin by identifying which BI features will provide the most value for your users. Whether it’s KPI dashboards for executives, embedded analytics for customers, or self-service reporting for your teams, Querio has you covered. Connect Querio to your data warehouse using read-only access, define your business logic within the context layer, and use APIs and theme tokens to build dashboards that seamlessly match your product’s design system.

To see results firsthand, consider launching a pilot program with stakeholders from various departments. For instance, Zim reported saving 7-10 hours per week on manual data tasks thanks to Querio’s natural language querying. With pricing starting at $1,100 per month and a money-back guarantee, you can test Querio’s capabilities without committing long-term. The sooner you implement governed, scalable BI, the faster your team can focus on what really matters - building and enhancing your product.

FAQs

How does Querio keep data secure and ensure compliance with regulations?

Querio prioritizes data security and compliance, embedding these principles deeply into its analytics platform. With integrated governance rules, the platform ensures that data access and usage are tightly regulated. Only authorized users can view or manage specific datasets, striking a balance between delivering precise insights and upholding robust security measures.

To further strengthen its security posture, Querio offers an enterprise-level framework featuring encryption, role-based access controls, and audit tools. These capabilities help organizations seamlessly integrate BI into their products while meeting industry regulations and protecting sensitive data from potential risks.

How do I connect Querio to my data warehouse?

If you're looking to connect Querio to a data warehouse, specific step-by-step instructions aren't outlined in the existing resources. Your best bet is to consult Querio’s official documentation or onboarding materials, as these will provide the most current and reliable guidance. For more personalized support, consider contacting Querio’s support team - they can offer direct assistance tailored to your needs.

Can I use Querio's AI-powered Python notebooks for advanced data analysis?

Querio’s AI-powered Python notebooks, known as agentic notebooks, are built for advanced data analysis. They provide a seamless way to explore, visualize, and analyze data - all within a secure and well-governed environment.

With intelligent tools at your fingertips, these notebooks simplify complex workflows, helping you uncover insights more quickly and make informed decisions, all while keeping complete control over the analytical process.

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