As the volume of data increases, the data environment becomes more complex. It can become increasingly difficult for organizations to prepare and store data, make it available to users, and set rules for incoming data. These data management challenges limit the use of and prevent getting the most from organizational data.
To improve the use of data, metadata is essential for companies. It makes working with data easier as metadata provides the necessary information about other data such as:
- how data is structured
- when data was generated or modified
- where data is stored
- who generated the data
- who has access to the data
Metadata enables simplified data management for businesses. So, it is important for data and analytics leaders to have a solid metadata management plan.
Best practices for metadata management
1. Define a metadata strategy
Metadata management strategy must be clearly defined and aligned with the business’s goals and vision. Here are some questions to consider when developing a strategy for metadata management:
- What kind of metadata is required to achieve business objectives?
- Are the company’s technological capabilities sufficient to support the metadata strategy? Technological capabilities consist of technical and managerial information and skills. Developing a metadata administration team that has experience with data management is essential to implementing a metadata management strategy.
- Where is the current metadata stored, and where will it be stored? How will metadata be maintained, and who will be responsible for it?
2. Define the scale of metadata management
Identifying critical use cases and prioritizing them is a best practice to set the right direction for implementing the metadata management strategy. It is important to align the metadata management strategy with the use cases and extend it to all departments.
As the size of the project increases, the complexity and risk of the project increase as well. Having metadata management guidance for specific use cases will help project managers and provide visibility over the use case. The steps for creating a framework for a specific metadata use case includes:
- Identifying and understanding the requirements of the use case.
- Defining the level of effort for the use case
- Evaluation of experience and knowledge of staff
- Determination of the financial resources involved for the use case
- Deciding if the problem is easily understood within the team, and the solution is difficult to achieve for the use case.
3. Adopt metadata standards to ensure data is used correctly
A metadata management standard is a document that contains principles and implementations to ensure data is used properly by its users. For instance, Dublin Core Metadata Element Set is one of the best-known metadata standards. consists of fifteen metadata elements that provide digital cataloging information about the digital resource or website. It enables a metadata schema that includes:
- Title: A name given to the resource to describe and identify it
- Subject: The topic of the digital resource
- Creator: The owner and generator of the resource
- Format: The file format
4. Choose appropriate metadata tools
The choice of metadata management tool depends on the approaches taken by businesses and their use cases. Based on the scope of use cases, strategies, business purposes, and technology infrastructure, you can identify the most important key functionalities and choose the right tool for your business. You should:
- Determine what data your organization has.
- Identify data sources and the flow of data between teams/departments.
- If you have any data governance restrictions, describe the rules and policies for organizational data.
- Define the scope of the use case.
- Determine main objectives
- Identify the limitations
- Define the process requirements
- Set deadlines
The 10 most popular tools for metadata management
- IBM Watson Knowledge Catalog
- Provides a unified data catalog platform to find, categorize and share data.
- Automatically organizes and transforms data to provide the right context, and prevents data dispersed among various silos.
- Provides ease of use for data stewards, data admins, and end-users.
- Automatically detects data sources and provides a single environment for accessing all data.
- Provides visibility over data, users can easily see how the data has been changed, transformed, and shared.
- Provides a centralized platform for metadata management.
- Describes the data source, its format, and its relationship to other data.
- E Enables customizations to create your own concept, and easy to integrate with other tools.
- Provides a single location to find, understand and manage data.
- Informatica Enterprise Data Catalog
- Provides an AI-powered data catalog to automatically scan metadata.
- Tracks data movement and assists in organizing and managing metadata.
- Automates data curation and discovery and provides users with a unified data catalog.
- Oracle Enterprise Metadata Management:
- A comprehensive metadata management platform. Can be integrated with other business intelligence tools such as Tableau, Power BI, etc.
- Enables interactive searching and browsing of metadata.
- More suitable for technicians as the technical nature of the tool is somewhat complex for business users.
- AWS Glue
- Aa serverless data integration service.
- Assists in extracting data from various sources, preparing and combining it for analytics.
- Data integration tasks such as extraction, cleansing, and loading are automated. AWS Glue allows different groups across an organization to collaborate on data integration tasks.
- To find data across multiple data stores, it creates a unified catalog.
- Alex Solutions
- Provides a unified enterprise data catalog for securely finding and using data.
- Suitable for business users as it offers ease of use.
- Provides unified access to data, connecting different types of data such as semi-structured, unstructured, and structured data sources.
- Connects different types of data sources such as enterprise, cloud, then combines them and delivers data to related internal platforms.
- People who are familiar with SQL will have no difficulty working with Aginity, as the front-end coding is written in SQL.
- Easy to set up multiple databases and perform queries from a single tool.
- Infogix Data360 Govern
- A metadata management solution that makes it easier for users to find and understand data.
- Automates data governance and enables collaboration across the entire business.
- Visualizes data flows and reports when a problem occurs.
If you would like to leverage a data management solution for your business, we have prepared a data-driven list of vendors.
We would like to answer your further questions regarding metadata management:
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