In today’s fast-evolving digital landscape, businesses are relying more than ever on data to drive decisions, gain competitive advantages, and optimize operational efficiency. For professionals in industries like real estate, PropTech, insurance, and investments, harnessing business intelligence (BI) effectively is no longer optional – it’s essential. However, the challenge of integrating, structuring, and maintaining high-quality data across diverse systems can be daunting.
This article delves into the transformative power of scalable BI and highlights a modern approach to data integration architecture – the BI mini-service model. By adopting this method, organizations can streamline data processes, eliminate inefficiencies, and unlock actionable insights faster.
Understanding the Need for Scalable BI Solutions
At the heart of any BI initiative lies the goal of making informed, data-driven decisions. But to achieve this, businesses need clean, structured, and high-quality data retrieved from an array of systems. Most organizations operate in hybrid environments where some systems are on-premises while others are cloud-based. This creates challenges in accessing and harmonizing data efficiently.
Osmo Vilen, Chief Product Officer of the Friends Integration Platform, emphasizes the criticality of integration platforms in addressing these challenges. As he explains, modern BI architectures must:
- Provide seamless integration between cloud and on-premises systems.
- Structure and link data for meaningful insights.
- Ensure data quality through rigorous validation processes.
What sets scalable BI solutions apart is their ability to deliver incremental value from day one. Instead of embarking on year-long data modeling projects, modern BI frameworks focus on delivering value quickly and iteratively.
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The Modern BI Architecture: A Shift from Traditional Models
Traditional data integration approaches often rely on tightly coupled systems, master data modeling, and rigid schemas with foreign keys and primary keys. While effective in the past, these methods are ill-suited to the demands of today’s dynamic business environments.
Modern BI architectures, akin to microservices, adopt a decoupled and scalable design. This is where BI mini-services come into play. These mini-services:
- Operate independently to handle specific data sets (e.g., customer data, revenue data).
- Avoid rigid relational data structures, instead relying on real-world relationships within the data itself.
- Facilitate both real-time and batch data processing for flexibility.
"Think of BI mini-services as modular components", Vilen explains. "Each focuses on transforming a specific aspect of your data, making it usable and insightful, while ensuring scalability and adaptability."
The Core Pillars of BI Mini-Services
To successfully implement the BI mini-service approach, organizations must focus on three key aspects:
1. Data Integration
BI mini-services connect to various systems – whether they are on-premises or in the cloud – to access data. This integration ensures that all necessary data sources are tapped into efficiently.
For example:
- A CRM might act as the master source for customer data.
- An ERP system could hold financial records or revenue data.
- Workforce management tools might provide employee-related information.
Integration platforms like Friends employ advanced tools such as pre-built connectors and APIs to streamline this process. Data is extracted, validated, and routed to the appropriate BI tool for analysis.
2. Data Structuring
The data retrieved must be structured and linked meaningfully. However, modern architectures avoid imposing artificial relationships (e.g., mandatory foreign keys). Instead, they use natural, real-world connections like email domains or website URLs to link datasets.
For instance:
- A customer’s email domain might serve as a linking factor between CRM customer records and ERP sales data.
- This approach minimizes dependency issues while ensuring meaningful relationships are maintained.
3. Data Quality
High data quality is non-negotiable. BI mini-services apply validation "quality gates" to ensure that only clean, usable data enters the system. Invalid data is flagged and sent to the source system for correction. This iterative process improves data quality over time without disrupting ongoing operations.
Advantages of BI Mini-Services
The BI mini-service approach offers several significant benefits over traditional BI models:
- Incremental Value Delivery: Unlike massive data modeling projects, mini-services allow businesses to start generating insights from day one, gradually expanding and refining capabilities.
- Scalability: Each mini-service operates independently, enabling organizations to scale specific components without overhauling the entire system.
- Flexibility: Real-time streaming and batch processing options ensure adaptability to various business needs and data scenarios.
- Improved Data Quality: Continuous validation and feedback loops help organizations improve the accuracy and completeness of their data over time.
- Ease of Maintenance: Decoupled architecture makes debugging, updating, and maintaining BI solutions faster and simpler.
Practical Applications of the BI Mini-Service Model
Case Study 1: Customer Data Integration
Imagine a scenario where customer data exists across multiple systems, such as CRM for contact details and ERP for sales records. A BI mini-service can:
- Extract relevant data from each system.
- Validate and harmonize the information (e.g., ensuring every customer record has a valid website and account owner).
- Populate a centralized data warehouse for analysis using tools like Power BI or Tableau.
Case Study 2: Tracking Project Metrics with Jira
A more complex example involves tracking project issue statuses in Jira. While Jira’s API may not provide direct metrics on how long a ticket spends in each status, a BI mini-service can:
- Fetch change logs for specific tickets.
- Calculate the duration of each ticket’s status transitions by analyzing timestamps.
- Feed this data into a reporting tool to provide actionable insights, such as identifying bottlenecks in project workflows.
These examples highlight the versatility of BI mini-services, capable of handling both straightforward and intricate data challenges.
Key Takeaways
- Start Small, Scale Big: The BI mini-service model emphasizes building smaller, independent components that can be scaled incrementally to meet growing needs.
- Focus on Real-World Relationships: Avoid rigid data schemas; instead, use natural relationships within the data for better flexibility.
- Embrace Incremental Value: Deliver value from day one, even if the data isn’t perfect. Over time, iteratively improve both coverage and quality.
- Enable Real-Time Insights: Combine batch processing with real-time streaming to ensure timely updates and actionable insights.
- Use Modern BI Tools: Tools like Power BI, Tableau, or QlikView allow for sophisticated relationship modeling and advanced data visualization directly within the BI layer.
- Centralize Data Validation: Perform quality checks within the BI mini-service and fix errors at the source system to maintain data integrity.
Conclusion
The modern world of business intelligence demands innovative approaches to data integration and reporting. The BI mini-service model provides a flexible, scalable, and efficient framework for organizations to unlock the full potential of their data.
For professionals in real estate, PropTech, insurance, and similar industries, adopting this approach isn’t just about staying current – it’s about leading the charge in leveraging data for strategic growth. By breaking down silos, focusing on high-quality data, and enabling real-time insights, organizations can make smarter, faster, and more informed decisions in an increasingly data-driven world.
Source: "Streamlining Data-driven leadership: How Integration platforms become the tools for BI & Reporting" – Frends – Integration Platform, YouTube, Nov 12, 2025 – https://www.youtube.com/watch?v=kn6QUkcV-qc
