Faced with the flood of data that companies are confronted with nowadays, it is necessary for them to acquire new tools and practices to exploit these new and important resources. One important tasks is managing metadata well. This blog post introduces the most important components a metadata management framework should consist of, with best practices to enable a harmonized implementation of metadata management.
Metadata is data about the data which provides basic information such as the creation types, the size or the changes occurred to certain data. In our last blog post, we described the metadata management process and its advantages for the stakeholders and their related business. A robust metadata management strategy ensures that an organization’s data is of high quality, consistent and accurate across their system landscape.
When using a comprehensive metadata management strategy, stakeholders are more likely to make business decisions based on correct data than those without a metadata management solution in place. Due to achieved higher data quality, the trust in the underlying data increases, and business decisions can be made faster. In the end, this allows a more agile organization and improves the added value significantly. Knowing this, other questions remain unanswered. How can an organization implement such a strategy from scratch? How can we ensure a comprehensive structured metadata management solution across all the organization?
The Most Critical Pain Points Regarding Metadata Management
Nowadays, the data collected by companies is becoming more and more complex and is stored on an unprecedented scale. This data is usually provided and used in different systems and tools across the same company or even in multiple organizations. This leads to a high effort in identifying relevant data and gaining insights. For example, a business user is not able to find the relevant data to complete his tasks without the help of IT specialists. Additionally, business users face problems in understanding data or sharing knowledge due to limited information access or missing governance. This process lacks efficiency and transparency.
Metadata Management Framework: Why It Is Needed?
A metadata management framework provides a concept and selection of tools for an efficient management and usage of metadata throughout the organization. Using a metadata management framework has several benefits and can boost your performance in processing data efficiently. It empowers you with the organizational structure and necessary tools to manage your data in a standardized way, so that the business users can find data easily and share their knowledge across the organization in full transparency and clear governance. The customizable solution contributes to more flexibility to meet the specific needs of a company, enhancing productivity and the efficiency of the business value extraction. A study published by Gartner advises organizations to use a role-based framework to organize and process their metadata, in order to increase their data processing performance and business intelligence. Furthermore, a powerful metadata management framework must be flexible to adopt new technologies, scalable to respond to business demands, and customizable to align with the organizational data strategy. Figure 1 represents some selected key advantages and use cases resulting out of a metadata management framework.
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Figure 1: Advantages and use cases of the metadata management framework
Core Components and Necessary Steps a Metadata Management Framework
As stated previously, a metadata management framework must be customizable and flexible to meet the specific need of an organization. It should also be scalable to respond to business demand and allow the use of new technologies. The framework should consist of core components and functionalities that help determine an organization’s as-is situation in order to derive its best metadata management strategy. The core components include organization, processes, data, systems, and tools. Only if these components are aligned and implemented synchronously, the derived metadata management strategy can be realized successfully. The implemented metadata management framework and its integrated functionalities will then help to make data searchable, usable, and manageable and to support business semantics. It also allows data consumers to quickly access trusted data and facilitate automated data management for data stewards. In the following, a guide of steps for designing a metadata management framework according to the needs of the organization is presented. Figure 2 gives a short overview of the different steps.
The first step is an as-is-analysis of the existing information management system and conduction of a metadata maturity assessment based on the core components organization, processes, data, systems, and tools. The goal is to derive the maturity of the organization in terms of metadata management. For this reason, the business process-related drivers to capture and store data and the data definitions across the process landscape are evaluated. By analyzing the data sources and the data flow within the organization, existing metadata such as business or technical metadata and existing processes such as metadata identification and creation processes are identified. Furthermore, the organizational structure and potential existing users’ roles related to metadata such as data architect, product owner or data steward are identified, and the relevance and completeness of the roles is analyzed. Lastly, the existing tools and systems are assessed regarding their relevance in metadata management and if they are sufficient to cover requirements to capture, store, and transfer metadata.
The second step is a goal clarification. Here, the metadata management requirements are collected through the organization by conducting interviews and workshops with the relevant key stakeholders. The aim of this step is to evaluate the customer needs and specific goals by identifying current gaps and deriving a prioritization of the goals. The goals should be based on the previously mentioned core components and the desired metadata functionalities. The outcome should be a prioritized list of identified goals.
The third step serves the conception of an individual metadata management framework based on the outputs of the previous steps and the prioritized goals and metadata functionalities. The design of the framework illustrates a harmonized view on the core components organization, processes, data, systems, and tools. The outcome of this step is a to-be metadata management framework design and a compatible implementation roadmap to achieve it.
As a fourth step, a tool assessment and selection are performed. The goal of this step is to identify and select the metadata management tool(s) that fit best the specific criteria and needs of the organization. Metadata solutions include generally various tools and features such as metadata repositories, business glossaries, data lineage, impact analysis features or semantic frameworks. This selection activity is important to achieve a customized solution that answers the specific needs of the organization. After the tool selection, the designed framework can be implemented.
By following these steps, you can create a metadata framework that is customized to your organization and that contribute to the efficient achievement of its goals. Our experts at CAMELOT can offer you the support needed to add value to your data and accompany you through your journey towards managing and choosing the best solution for your metadata.
We would like to thank Stefan Morgenweck for his valuable contribution to this article.
