Metadata: With the rise of data analysts and scientists, producing specific information for any business has become more accessible.
In this way, managers can strengthen their commercial strategies, armed with the knowledge they did not have before.
However, metadata management provides essential information for the business. In this post, we will introduce the concept and how effective management of these assets enables several benefits. Follow us!
What Is Metadata?
Metadata describes the various facets of an information asset, which enhances the usability of that element throughout its lifecycle. Furthermore, they provide a superior level of understanding for the professionals who handle them.
This means that specific data can be reused and recovered, increasing its applicability for numerous business use types. In short, metadata is data (information) about data.
And where can they be found? In virtually any element of technology infrastructure, robust or otherwise. They exist in header structures, legacy systems, miscellaneous configuration files, the cloud, and social media.
Technical metadata provides some simple examples: columns from a given table in a database and validation keys. In addition, there is so-called business metadata, which different levels of security can represent.
The main difference between metadata and data is that the former details instances or non-specific records. They are similar in that both the IT sector of a business and the finance department, for example, use them to seek more knowledge within the existing technology infrastructure.
Other, more straightforward examples involve elements of people’s daily lives: the date and time accompanying a digital image file are metadata, just like tags linked to a blog article.
This is because they also offer a description of the structure of the primary data, offering additional and relevant information about that element.
What Are The Benefits Of Metadata Management?
The information is processed, consulted, and updated from the metadata in a technology system. In this way, it will be easier to understand how the data was generated and more accurately map the environments in which it resided.
They also function as a meticulous record of changes made to the data. Thus, it becomes easier to understand how users are manipulating them.
It is important to note that documenting your data efficiently avoids problems when producing business-relevant knowledge.
They enrich the data so software solutions can precisely interact with the information. Thus, preserving the meaning of elements outside their original contexts is possible.
How To Carry Out This Management?
Companies reap the rewards of an accurate metadata governance strategy. This is because they provide better-informed decisions. With this type of management, the company gets a more accurate view of the data flow within the organization.
Now, let’s learn the steps of an effective metadata management job. The tools must be robust enough to provide information access and align with business guidelines.
Sample data, a term in English that describes an initial testing period, is the first step in a metadata management strategy.
This is the time to generate samples to define the context of the operation with metadata. It is a visualization work that gives managers a deeper understanding of these elements.
Data Stats (Statistics)
Statistics and models developed by scientists and data analysts will answer questions such as the count and minimum and maximum values of that particular metadata.
Lineage helps specialized professionals and business managers understand the origins of data. In addition, they understand how these elements “traveled,” that is, circulated through the company’s systems.
Finally, it is possible to identify the various transformations that occurred with this metadata. The final stage of this step is to provide an understanding of where these elements are being used.
Communication Between Professionals
Communication is the key to effective metadata management. Therefore, it is essential to link all operations being carried out. In this way, the joint production of insights enables the integration and production of information aligned with the company’s objectives.
Relationship With Other Metadata
This functionality must be respected by any management tool. This is because a direct relationship between the different metadata that circulate in a system is crucial, making searching and transforming these elements into relevant knowledge possible.
There are several ways to achieve this phase: manually, through human work, or automatically. In this last method, there is a search for semantic correspondences to other elements already existing in the system.
AWS’s Role In The Process
Amazon’s service platform, AWS, provides various solutions for metadata management work. The AWS Glue suite, for example, provides a repository that operates across numerous data extraction sources.
Glue connects to other Glue solutions such as Amazon EMR, Amazon RDS, and Amazon Redshift. Also known as the Data Catalog, Glue can work with a suite like Apache Atlas.
In addition, tools such as IP sense Cloud Content Manager manage digital content directly in the cloud, further modernizing the system. With this program, it is possible to solve questions related to the following factors:
- recovery of content in large quantities.
This digital solution uses an ACL Access Control List, which defines access permissions according to each user and system component. It is based on repositories, metadata, and other types of documents.
As we can see in the post, metadata management is a means of extracting a more significant amount of information from a specific piece of data. In addition, it is possible to establish the history of that virtual asset, understanding its changes over time and making a recovery easier.