This blog was co-authored by Dan Merzlyak and Dave Stone
Today’s businesses have access to more data than ever before, but the real challenge lies in efficiently finding, organizing, and deriving actionable insights from this vast information landscape. The divide between thriving companies and those struggling to keep pace is increasingly defined by their ability to transform raw data into strategic advantage. Time-to-insights is crucial, organizations grapple with the dual challenges of managing diverse data sources and extracting meaningful intelligence in a timely fashion. This blog explores how EDB's Mission Control platform, powered by EDB Postgres AI, is leveraging Postgres as a Lakehouse. By consolidating data silos, enabling real-time decision-making, and providing a unified view of business performance, our Mission Control platform is helping our teams achieve unprecedented levels of operational efficiency and customer engagement.
Key results EDB has achieved by building its Mission Control business analytics platform on EDB Postgres AI
As the SVP of Data Analytics & AI at EDB and with previous experience in the finance industry, I've seen firsthand how unified data analytics can reshape decision-making. At EDB, we're adopting a revolutionary approach to streamlining business intelligence with a Postgres Lakehouse architecture. By modernizing legacy systems and eliminating data silos, we’re enabling cross-channel consistency and accelerated decision-making. This foundation, driven by our Mission Control solution, is paving the way for transformative use cases that prove the impact of a Postgres lakehouse.
What's the Postgres Lakehouse Impact?
Netflix, a known user of Postgres, likely harnesses this powerful database as a Lakehouse to speed up content creation and streamline business operations. How? From my lens, they leverage Postgres to gain a unified platform for ingesting and processing vast amounts of structured and unstructured data — from viewing habits and social media trends to production costs and talent analytics. By leveraging the Lakehouse’s ability to perform complex queries across diverse data sets, Netflix can then predict the next big hit with uncanny accuracy. This data-driven approach might have led to the perfectly timed, nostalgia-filled release of “Stranger Things.”
Postgres Lakehouse with Mission Control
The Data Dilemma: Overcoming Silos and Fragmentation
Similar to many finance companies I’ve worked with, EDB faced the common challenge of data silos, where critical information was dispersed across various departments, making it difficult to access a unified view of business performance. This fragmentation often led to delays in reporting, inconsistencies in data interpretation, and ultimately hindered our ability to make timely, informed decisions.
Mission Control: Building a Single Source of Truth
Recognizing the need for a more integrated approach, we embarked on creating Mission Control — a centralized repository of dashboards built on EDB Postgres AI, designed to provide a single source of truth for data reporting and analytics. By consolidating data from diverse sources like Marketing, Finance, HR, and Product into one cohesive system, we now have real-time visibility and the ability to deliver actionable insights at every level of our organization. This transformation has enhanced our operational efficiency and empowered our teams to make strategic decisions with greater confidence and precision.
From Data Integration to Customer Insights
Integrating all of this data was essential to creating a holistic view of our operations and building a robust Lakehouse framework. By combining data from various sources, we can track the entire customer journey, enabling us to understand and predict customer behavior with far greater accuracy and offer exceptional, personalized service.
“Our transition to EDB Postgres AI has been transformative. The speed and efficiency with which we can now process and analyze data to drive real commercial outcomes are unparalleled," says Herve Timsit, EDB Chief Revenue Officer.
This unified data approach empowers us to deliver personalized experiences, improve customer satisfaction, and drive deeper engagement. Now, internal teams can access the same insights, leading to better strategic alignment and more informed decision-making across the organization. Our value from integration is not just in improving customer interactions, but fostering data-driven growth throughout the business.
Mission Control in Action
Mission Control: where data meets crystal ball, minus the fortune-teller's outfit and cryptic predictions. It's like giving your business a superpower, but instead of flying on a magic carpet, you're soaring through data. Equipped with a reliable platform for comprehensive insights, there are an infinite number of new ways we can leverage data to accelerate our business. Read the use cases below to see three ways we’re taking action now.
Strategic Decision Making: Using historical data from our Mission Control dashboards, we can identify long-term trends and inform high-level business strategies and planning. This capability is particularly beneficial during key meetings such as Performance Model Reviews and Quarterly Business Reviews.
Tactical Analysis: For short-term goals and performance monitoring, Mission Control allows us to analyze areas for immediate improvement or action. The ability to drill down into specific data segments with customized filters provides precise and actionable insights.
Operational Monitoring: The real-time data tracking feature of Mission Control is instrumental for optimizing daily business operations. By monitoring live data, we can swiftly address issues and ensure operational efficiency.
Additionally, Postgres has many extensions and integrations that allow us to support a variety new use cases:
- Pgvector: AI business intelligence and revenue enablement
- Time Series Data: Historical with real-time data analysis.
- Data Integration: All of your data in single data store
- Search Capabilities: Analyze unstructured and structured data quickly
Results of Analytics on Postgres
EDB Postgres AI vs. Proprietary Databases: A Cost-Efficiency Analysis
Building analytics with similar business intelligence capabilities can be achieved with other databases. However, my team discovered significant cost and efficiency advantages using EDB Postgres AI. Proprietary databases often come with high licensing fees, rigid scalability options, and complex configurations, which can slow down operations and drive up costs.
EDB Postgres AI, on the other hand, is built on open-source Postgres, which provides the flexibility to scale up or down based on business needs without the associated costs of enterprise-level databases. Moreover, Postgres allows us to tap into a broader ecosystem of tools while benefiting from ongoing innovation and community support. This combination allows us to achieve the same — if not better — performance for a fraction of the cost, making it a far more efficient and scalable choice.
Real-World Impact: EDB Postgres AI
Modernization and Speed to Value: EDB Postgres AI has turbocharged our data warehouse, slashing query runtimes by 50-90%. This acceleration delivers timely insights aligned with our business rhythms.
Real-Time Data Insights: Mission Control dashboards leverage EDB Postgres AI for immediate operational visibility, enabling swift optimization and issue response. This real-time capability is crucial for tactical analysis and operational monitoring.
Data Enrichment and Optimization: We've expanded our data estate with new sources, tables, and fields, creating a comprehensive environment for reporting and metrics. This enriched ecosystem supports both analytical and transactional workloads for strategic decision-making.
Distributed High-Availability: EDB Postgres AI Clusters enables geographically distributed databases, enhancing disaster recovery and ensuring high availability. This setup is vital for business continuity in our global operations.
Future-Proofing: EDB Postgres AI's flexibility future-proofs our infrastructure for advanced use cases. For instance, in Account Risk Prediction, it provides the computational power to develop churn prediction models, supporting proactive customer retention efforts.
The Road Ahead: Embracing the Future of Data Analytics and AI
Lakehouse Analytics through Mission Control on EDB Postgres AI exemplifies our commitment to innovation and excellence in data management and analytics. By harnessing the power of real-time data insights, enriched data environments, and high-availability clusters, we are well-equipped to meet the demands of modern data and analytics infrastructures and future-proof for new AI workloads.
To learn more about how EDB Postgres AI can transform your data management and analytics capabilities, visit the EDB Postgres AI home page.