How a Risk Management Firm Achieved 50–70% Faster Data Processing with Medallion Architecture
Client Background A Leading Risk Management Services firm, with expertise in compliance monitoring, fraud detection, and financial risk assessments, was held back by on-premises SQL Server and rigid SSIS pipelines. The fragmented data across ERP, CRM, PostgreSQL, and SQL Server systems, lead to scalability issues, inconsistent reporting, and heightened compliance risks due to absence of governance and version control. Project Objectives Solution & Implementation We reimagined the client’s data ecosystem using Azure and Databricks, with the Medallion Architecture (Bronze → Silver → Gold) at the core: The Data Modernization Journey Impact Delivered
Transforming Operations with Databricks for Food and Beverage: How F&B Industry Is Gaining a Data Advantage
The U.S. Food & Beverage industry, valued at over $1.5 trillion, is embracing digital transformation at scale. With rising consumer expectations, regulatory pressures, and complex supply chains, data is now at the center of smarter operations. That’s where Databricks for Food and Beverage comes in, empowering companies to unify, analyze, and act on their data like never before. Data Challenges faced by F&B Industry The F&B industry deals with a wide variety of data which includes managing the data of factories, retail, and customers. Here are some of the key challenges in terms of data management- Why Databricks for Food and Beverage? Core Capabilities for the Industry 1. Lakehouse Architecture: Simplifying Data Storage and Access Lakehouse is a hybrid model that merges the flexibility of data lakes with the performance and reliability of data warehouses. Data comes from multiple sources like production sensors, supply chains, retail POS systems, customer feedback, and more. All this data can be stored, cleaned and analyzed through Lakehouse. Additionally, there’s no need to move it between multiple systems, which saves time and reduces errors. Explore our deep-dive on migration from traditional warehouses to the Databricks Lakehouse to see why it plays a major role. 2. Unified Platform for Engineering, Data Science, and Business Intelligence Databricks for Food and Beverage enables multiple teams to work on the same platform using the same data. For instance- Data Engineers can use Apache Spark to build and automate pipelines to move and clean data. Data Scientists can explore data, build models, and test machine learning algorithms directly from notebooks. Business Analysts can connect BI tools (like Power BI, Tableau, or Databricks SQL) to manage and deliver real-time dashboards. 3. AI and MLOps Integration: From Experiments to Production Building and Deploying Machine Learning models is easy with Databricks. 4. Built-In Governance: Delta Lake and Unity Catalog As data volumes grow, focus on security, compliance, and data quality increases. Databricks addresses this with built-in governance tools: Delta Lake handles data version control, transaction support (ACID), and schema enforcement which helps in keeping the data clean, consistent, and recoverable. Unity Catalog is a uniform governance layer that helps you manage access to data, track data lineage, and ensure audit readiness. These features ensure the right people have access to the right data without any error. Databricks for Food and Beverage Industry Databricks for Food and Beverage is revolutionizing the industry by driving production efficiency, enhancing quality control, and enabling predictive maintenance. By analyzing machine sensor data, companies are able to detect equipment failures before they happen, reducing downtime. Furthermore, supply chain analytics helps manufacturers by optimizing procurement, production planning, and inventory management. Key Impact Areas: Databricks for Food and Beverage: A Step-by-Step Process Guide The journey of data on the Databricks platform typically follows a streamlined, end-to-end process: Data Ingestion & Integration: In the F&B sector, Databricks for Food and Beverage captures data flowing from farm-level smart sensors, ERP systems on factory floors, retail POS terminals, social media feedback, customer reviews, logistics networks, and even external feeds such as weather forecasts turning every touchpoint into actionable insight. Databricks uses powerful tools like Apache Spark, Auto Loader, and Delta Live Tables to gather this data in real time or in scheduled batches. This helps businesses process large volumes of complex data efficiently and arrive at conclusions. Data Storage & Governance (Delta Lake & Unity Catalog): Once the data is collected, the data is stored in a secure, organized, and accessible manner. In the F&B industry, this is particularly important as the data pertaining to supplier contracts is sensitive, and regulatory compliance such as food safety records is a compulsion. For this to be possible, Delta Lake acts as a reliable storage layer with support for ACID transactions. This ensures that every change to the data is accurate and traceable. It also allows schema enforcement, so unexpected data types don’t break the system. Data Engineering & Transformation: Data engineers working in Databricks use PySpark, SQL, Scala, or R to clean, join, and enrich the data. They work in collaborative notebooks that allow cross-functional teams (like supply chain, sales, and marketing) to build a clear picture of their business. For the F&B industry, this step is crucial to support: Data Science & Machine Learning: Tools: MLflow, scikit-learn, TensorFlow, PyTorch, Databricks Machine Learning. Once the data is structured and organized in specific sets F&B companies apply machine learning (ML) to extract deeper insights. Databricks provides an end-to-end MLOps environment that supports building, training, and deploying models all in one place. Some ML applications in the F&B industry comprise of predicting the demand before seasonal changes or festive season, computer vision to identify the defects in products during manufacturing, forecasting the shelf life of perishable goods among others. Business Intelligence & Visualization: The final and most important part of the workflow is wherein the insights are delivered to business leaders and frontline teams. This helps the top management to decide on launching a new product, enhance or optimize the factory output or solve a logistic issue. With Databricks SQL and integrations with tools like Power BI, Tableau, and Looker, companies can create dashboards that visualize daily production performance, identify sales by region or specific product, drive real-time delivery metrics and energy consumption of specific plant in the manufacturing unit. Databricks for Food and Beverage: How Companies Across the Value Chain Drive Real Outcomes Databricks plays a pivotal role in every segment of the F&B industry with giant companies across the globe utilizing it to enhance their performance. One such example is- Pepsico, the company faced a major and common challenge wherein the data spread across multiple systems caused duplication and inefficiencies. To solve this issue, the company planned to unify global data under a single architecture to access real-time insights and improve customer service. This would automatically boost their sales and help them in business. By moving from descriptive to predictive and prescriptive analytics, PepsiCo started using AI and machine learning to make better decisions like