Enhancing Real-Time Analytics and Multi-Modal Search for FMCG Distribution

Business Context

The customer provides a digital business management system tailored for fast-moving consumer goods (FMCG) distributors. This system standardizes processes across procurement, warehousing, distribution, financial management, field operations, and customer management, helping distributors improve operational efficiency and decision-making through data-driven insights.

Core Functionalities

• Data-Driven Decision Support: Multi-dimensional data reports help identify risks related to sales, inventory, and financials, providing a scientific basis for decision-making.

• Comprehensive Business Process Management: Covers procurement, inventory, distribution, financials, market management, sales outreach, and reporting.

• Inventory Optimization: Real-time updates on stock levels and expiration dates reduce overstocking and shortages.

• Financial & Risk Control: Accounts receivable tracking, overdue reminders, and automated reconciliation lower financial risks.

• Product & Marketing Optimization: Sales reports by product and brand help refine product mix and marketing strategies.

• Seamless Online & Offline Operations: Integrates e-commerce store management with offline distribution.

• Intelligent Alerts: Automated notifications for stock shortages and expiring products improve operational efficiency.

• Delivery Efficiency Enhancement: Dynamic order-based route optimization improves order fulfillment capabilities.

The system aims to replace manual processes, reduce inefficiencies in inventory management, and enhance customer relationship management by leveraging real-time data and automation.

Original Architecture & Challenges

Legacy System Architecture

The customer's original system relied on a traditional data warehouse for structured data storage and Elasticsearch for full-text search. The architecture looked like this:

• 1. Data Ingestion & Storage

  • Transactional data (sales, inventory, orders) was batch-loaded into a cloud-based data warehouse for analytics.

  • Product descriptions and unstructured data were indexed in Elasticsearch for full-text search.

• 2. Query Execution & Reporting

  • Business intelligence (BI) tools queried structured data for reports and dashboards.

  • Elasticsearch queries handled product searches but could not filter by structured attributes like sales performance or stock levels.

Pain Points in the Original System

• Delayed Data Updates: Data synchronization across systems was slow, causing reconciliation mismatches and outdated reports.

• Slow OLAP Queries: Large-scale aggregations (e.g., sales trends, inventory turnover)suffered from high latency.

• Multi-Modal Search Inefficiency: Searching across both Elasticsearch and structured data in the warehouse required separate queries and manual data stitching.

• Scalability Bottlenecks: Increased data volumes led to slow query performance and system instability.

New Architecture with Tacnode

With Tacnode, the customer unified structured data and full-text search, enabling real-time analytics and efficient multi-modal search. The new architecture:

1. Real-Time Data Processing

• Tacnode ingests structured, semi-structured (JSON), and unstructured (full-text) data in real time, replacing the previous batch-loaded data warehouse while integrating directly with Elasticsearch for full-text capabilities.

• Unlike the legacy setup, structured business data and full-text search are now accessible in a single system, enabling instant analytics and seamless query execution.

2. Omni-Search: Unified Multi-Modal Queries

• Tacnode's Omni-Search natively integrates full-text search with structured OLAP queries, allowing users to perform hybrid searches across structured attributes and text-based product descriptions in a single query.

• This eliminates the need to query Elasticsearch separately and manually join results, significantly improving search efficiency.

3. High-Performance OLAP & Query Execution

• Materialized views and real-time aggregations replace slow batch-processing queries from the previous data warehouse.

• Massively parallel processing (MPP) speeds up analytical queries, improving performance for dashboards and reports.

4. Scalability Without System Complexity

• While Tacnode does not replace the customer's existing transactional database, it completely replaces their data warehouse and Elasticsearch for analytics and search.

• Separation of compute and storage ensures linear scaling, allowing high concurrency and low-latency queries even as data volume and traffic grow.

Benefits of the New Architecture

Tacnode's Solution & Impact

1. Real-Time Data Synchronization for Instant Business Insights

• Tacnode's high-concurrency, low-latency architecture ensured that business data was updated in real-time.

• Inventory updates were fully synchronized within seconds, eliminating discrepancies during stock reconciliation.

• Business dashboards instantly reflected the latest data, enabling proactive decision-making for inventory replenishment and sales strategy adjustments.

2. Fast OLAP Query Performance for Real-Time Analytics

• With Tacnode, query response times improved by 2x, significantly enhancing the user experience.

• Users could now generate interactive reports instantly, eliminating previous delays in filtering and visualization.

• Example: Dashboards that previously took several seconds to load now render results in real time, allowing teams to analyze business trends effortlessly.

3. Omni-Search: Unified Multi-Modal Search Across Structured and Full-Text Data

• Tacnode introduced Omni-Search, a solution that seamlessly integrates full-text search with structured OLAP queries, enabling users to perform hybrid searches across structured attributes and text-based product descriptions in a single query.

• This eliminated the need for manual data stitching between Elasticsearch and the data warehouse.

• Example: Users can now search for "orange juice" and instantly filter by sales performance and inventory status, retrieving results in milliseconds, a major improvement over the previous multi-step approach.

4. Horizontal Scalability & Long-Term System Stability

• Tacnode provided seamless horizontal scaling, allowing the system to handle increasing data volumes and user requests without performance degradation.

• The system automatically balanced workloads, ensuring smooth operation even as demand increased.

• Example: Despite a 15x increase in data volume and 4x higher traffic, Tacnode maintained stable and fast performance, ensuring uninterrupted service.

Business Outcomes

• Instant Business Insights: Real-time inventory updates eliminated reconciliation mismatches.

• Faster OLAP Query Performance: 2x improvement in query speeds resulted in a seamless, interactive user experience.

• Omni-Search Multi-Modal Query Efficiency: Integrated full-text and structured search into a single, fast query, eliminating manual stitching and inefficiencies.

• Scalability for Future Growth: The system now handles high traffic and large data volumes effortlessly, ensuring long-term stability.

Why Tacnode?

Tacnode's Postgres-compatible, distributed architecture provided a unified solution for real-time data ingestion, high-performance analytics, and multi-modal search. By introducing Omni-Search, it successfully solved the customer's data synchronization, query performance, search integration, and scalability challenges, making it the ideal choice for modern data-driven business platforms.