A Definitive Guide to Metadata Management
What is Metadata Management? Metadata is like a golden thread that interconnects different functions of an organization. It comprises heterogeneous, heavily distributed and hybrid mixes of data from cloud systems. Metadata management deals with the management of complex data through analytics, operations, discovery, collaboration, and compliance. Metadata management acts as a key enabler in the [...]READ MORE >>
What is Metadata Management?
Metadata is like a golden thread that interconnects different functions of an organization. It comprises heterogeneous, heavily distributed and hybrid mixes of data from cloud systems. Metadata management deals with the management of complex data through analytics, operations, discovery, collaboration, and compliance. Metadata management acts as a key enabler in the data-driven decision-making process of a business. For any organization, all the data-driven actions pass through metadata when the customers browse through the website, run a query or make a virtual view.
Businesses need to understand and analyze their data to survive and grow. Metadata management can provide the required processes to gain this insight and succeed. Want to know how? Get in touch with our experts.
Why is Metadata Management Important?
With the growing volume of data, metadata management has gained huge importance. Although it sounds a little geeky, it is a crucial component of records management and data governance. Here are a few reasons why metadata management is important:
Reason #1: Increases the longevity of datasets
The lifespan of a particular dataset can be very short due to the unavailability of relevant metadata. The growing complexity of data with the increasing constraints of time and funding also contributes to the shorter life span of the datasets. But metadata management can counteract this tendency of data degradation efficiently.
Reason #2: Facilitates data reuse and data sharing
Metadata management ensures that the complex and complicated data is easily analyzed, interpreted and shared. It provides detailed instructions to interpret unfamiliar data accurately and helps in data integration.
Reason #3: Helps in maintaining historical records of long-term datasets
The datasets may encounter inconsistency in methods and instrumentation during the ongoing long-term projects. Metadata management helps in maintaining the historical records of such long-term datasets, thereby assisting in data governance. Furthermore, metadata management is important for data integration that contains different parameters but shares common temporal or spatial domains.
Wondering how metadata management system can enable you to build an enterprise model based on the metadata developed from various attributes such as your data integration tools and data warehouse? Request a FREE proposal now!
Reason #4: Assists in improving interoperability and integrating resources
Metadata management makes it easy for humans as well as machines to understand the different resources. Also, it facilitates the understanding of how data is exchanged among many systems with different data structures, operating systems, and interfaces.
Reason #5: Protects resources and their future accessibility
The digital information today has become very fragile and is susceptible to corruption. Metadata management helps in archiving and preserving such information by tracking the lineage of the information and describing its characteristics. Also, it helps in understanding the behavior of the information to prevent its replication in the future.
Steps to Effective Metadata Management
Step #1: Meta repository creation
There are several repository tools available in the market that profess to create metadata repository. But all such tools may not suit your business. Most of these tools focus on one specific aspect of metadata. Therefore, you need to collect a set of metadata about each element of your business and relevant to your organization in the following six categories:
- Business metadata
- Core and technical metadata
- Data quality metadata
- Search metadata
- People metadata
Step #2: Identify core attributes
Develop key business queries to get a fair idea about the underlying attributes which is necessary for analysis. It is important to identify and understand such attributes as they play a crucial role in downstream analytics.
Step #3: Acquire the metadata
Once your foundational capabilities are established, the next step that comes is implementing the meta acquisition process. Most of the categories of metadata need proper processes for acquiring it from the people who work in various functions of the organization.
A properly built metadata management model has the potential to give a 360-degree view of how operating systems in your organization are connected together. Such models can help users to solve issues based on different attribute types and names. Request a free demo to know more about how metadata management models can help in creating custom metadata types.
Step #4: Create a protocol and maintain consistency
Data keeps on changing constantly with the growth of new business initiatives every day. Such changes result in long-term data instability. Therefore, it is necessary to create a more efficient process to monitor data streams for change. This is the most difficult but important step in establishing an effective metadata management process.
Metadata Management Vs Master data Management
Metadata management talks about the content in the data that is gathered and helps the organizations in uncovering the facts hooked to their data. Through metadata management, users can decode the data in terms of what it represents and derived. Metadata management consists of all the entities and attributes, programs, calculations, reports etc. The nature of metadata depends on what it talks about.
Master data management talks about the data that consists of entities like products, services, people, organizations etc. It usually talks about non-transactional data which usually covers:
- Internal entities such as employees, departments, and products
- External entities such as suppliers and customers
- Information of organization such as reporting hierarchies and the chart of accounts.
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