The financial industry in general and buy-side firms in particular are increasingly realizing the significance of efficient enterprise data management (EDM). Enterprise data management is essential to virtually every aspect of operations in buy-side firms. To understand the full potential of EDM to improve operational efficiency and decision-making processes, it is pivotal to define the reference architecture for enterprise data management. In this blog, we will explore what the reference architecture involves and why it is critical for efficient EDM.
Challenges in enterprise data management
In the complex financial landscape, data is at the heart of every strategic decision. Multiple factors make it difficult for buy-side firms to manage data efficiently and accurately. These include rising data volumes and outdated systems and processes. The lack of a centralized data management system further compounds these challenges, leading to what many decision-makers describe as “data chaos.” Symptoms of data chaos include difficulty in locating a specific piece of data, data delays, high rates of human error, and data discrepancies.
Understanding the importance of enterprise data management
Enterprise data management plays a crucial role in controlling data chaos and bringing harmony to highly complex financial operations on the buy side. EDM creates a consistent and reliable source of data across the organization, or a “single source of truth,” which is instrumental for informed decision-making processes. To quantify how buy-side firms understand the role of EDM, we conducted a survey of key decision-makers at select organizations. The poll provided a great deal of insight about enterprise data management efforts. For example, a staggering 86% of respondents said they find it hard or very hard to monitor data-related processes and analyze issues. These results demonstrate a glaring need for efficient enterprise data management solutions that facilitate smooth operations.
The importance of data quality
One important part of the EDM reference architecture is data quality, as defined by a data quality score that quantifies data accuracy, completeness, and consistency. The data quality score serves as an overall measure of data reliability as well as the efficiency of EDM. It is important to know your data quality score because high data quality generates reliable insights, fosters trust among stakeholders, and drives positive business outcomes. All of the survey respondents agree, with 100% saying they consider the data quality score as important, somewhat important, or extremely important. This result underscores the growing recognition of the need for high-quality, reliable data.
The necessity of data lineage
Another important element of EDM reference architecture is data lineage. Data lineage offers transparency in understanding where data originates, where it moves throughout its life cycle, and how it gets transformed along the way. Having a centralized EDM system in place gives buy-side firms access to accurate data lineage, allowing these firms to manage data more efficiently and make swift, informed decisions. In the fast-paced financial industry, this is a significant competitive advantage. Our survey found that only 14% of organizations have a centralized EDM system with real-time data lineage. This finding highlights the urgent need for more comprehensive and centralized enterprise data management systems.
Why centralized data discovery and consumption matter ?
Data discovery and consumption play a crucial role in leveraging data for a competitive advantage. Without a centralized system, however, buy-side firms will find it challenging to utilize data resources effectively. A centralized location for data discovery and consumption ensures that all relevant stakeholders can access the data they need as soon as they need it, facilitating efficient operations and faster decision-making. Unfortunately, our survey reveals that about 86% of organizations do not have centralized data discovery and consumption. This underutilization of data resources may hinder both growth and competitiveness.
Elements of effective data governance
Reference architecture for EDM also includes data governance, which involves all of the data quality checks, workflows, and stewardship required to ensure the reliability and accuracy of data and facilitate effective data management. Key elements of data governance include a well-defined governance structure, clear data ownership, consistent data standards, and effective data quality management. It is noteworthy that 100% of surveyed organizations view data governance as important for their firm. This resoundingly consistent feedback reinforces the fundamental role of data governance in effective enterprise data management.
The importance of enterprise data management (EDM) for buy-side firms can’t be overstated. As data volumes grow and operational complexity increases, a well-defined reference architecture for EDM — including data quality, data lineage, and data governance — will help firms compete more effectively in a data-driven world.
You can also read more blogs from IVP on a variety of topics.
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