The importance of enterprise data management (EDM) on the buy side cannot be overstated. Markets and investment decisions are data-driven, which is why buy-side firms must make sense of the continuous, voluminous flow of structured and unstructured data. Because of this, buy-side firms are reconsidering the need for an enterprise data management (EDM) system that enables accurate, timely, and informed decisions.
However, many firms struggle with questions and issues related to enterprise data management due to the lack of a reference architecture. In short, a reference architecture is a combination of documents, concepts, and best practices that recommend the optimal execution of a technology, in this case EDM. A reference architecture can help guide buy-side firms as they go about implementing a comprehensive and effective enterprise data management system.
Why a reference architecture for enterprise data management (EDM) is vital?
Most organizations find it hard to monitor data-related processes and analyze how well they perform (or how they underperform). This is a clear indication of the need for a centralized system that provides real-time data lineage and data discovery. Additionally, data quality scores are extremely important for understanding data accuracy. All of this highlights the need for data governance, including data quality checks, workflows, and data stewardship.
To address these challenges, buy-side firms need a reference architecture for enterprise data management (EDM). A reference architecture provides a comprehensive framework for data management to help buy-side firms:
● Access a blueprint for building an enterprise data management system
● Ensure data is managed in a consistent, standardized way at enterprise scale
● Facilitate the integration of data from various sources
● Enable real-time data lineage and data discovery
● Ensure data quality through data governance
Key Pillars of an EDM Reference Architecture
There are several pillars of an EDM reference architecture, including:
Data Fabric Architecture
Data fabric architecture enables organizations to implement modern data management practices. Data fabric leverages human and machine capabilities to access data in place or support its consolidation where appropriate. It continuously identifies and connects data from disparate applications to discover unique, business-relevant relationships between data points. These insights support faster decision-making, providing value through rapid data analysis.
Many leaders in data architecture have pivoted from a centralized enterprise data lake to “domain-driven” designs that can be customized and “fit for purpose” to improve time to market of new data products and services. In other words, domain-driven designs enable firms to build data models tailored to specific needs, rather than relying on a “one-size-fits-all” approach.
Master Data Management (MDM)
Master data management (MDM) enables firms to establish a trusted view of critical data and parameters. Broadly speaking, MDM includes three frameworks: registry architecture, hybrid architecture, and repository architecture. In this way, a well-designed master data management (MDM) system creates a “single source of truth” that helps firms make informed decisions based on trusted data more efficiently.
Data governance is the cornerstone of consistent and standardized data management practices. It is the key to upholding the highest standards of data quality through checks, workflows, and data stewardship. For asset managers, hedge funds, and private funds, establishing a robust data governance framework is extremely important. This framework ensures data is and remains of the highest quality, enabling more informed investment decisions that drive growth.
With a reference architecture for enterprise data management (EDM), buy-side firms can better understand the critical issues and take a more effective, decisive path to choosing a solution. A well-designed reference architecture not only provides a comprehensive framework for data management, but it enables firms to ensure EDM solutions can integrate data from various sources, ensure data quality, and facilitate real-time data lineage and data discovery. Ultimately, this will help firms establish a robust enterprise data management system that empowers them to make informed investment decisions based on accurate and timely data.
Learn more about how IVP can help your firm tackle modern data management challenges, including a reference architecture for enterprise data management.
You can also read more blogs from IVP on a variety of topics.
1. Gartner, “Data Fabric Architecture is Key to Modernizing Data Management and Integration,” May 11, 2021. Available at: https://www.gartner.com/smarterwithgartner/data-fabric-architecture-is-key-to-modernizing-data-management-and-integration
2. McKinsey Digital. “How to build a data architecture to drive innovation—today and tomorrow,” June 3, 2020. Available at: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/how-to-build-a-data-architecture-to-drive-innovation-today-and-tomorrow
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