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Metadata management is a very powerful and important practice in database management. With the recent rice in distributed database architectures like Cloud and Big, there is a surge of siloed data and systems. Metadata management has now become more crucial in managing enterprise information assets. You can find many articles and tips on the internet about metadata management, which may easily confuse the readers. In this blog, we are trying to explain metadata management in the simplest terms for easy understanding.
What is metadata management?
Let us start from the very basics. Even though there are many definitions for Metadata Management functionality is to enable a business user to search and find the key data over a web-based UI. For example, a customer ID can be a searchable key attribute. Having appropriate metadata management in place, the business users may easily understand where the data related to that attribute is and how it is calculated. Users can also easily visualize which systems in the enterprise use this attribute, and they may also understand the impact of changing something to the attribute.
Metadata management is also crucial for the technical users of the enterprise systems. Combining the technical metadata with business metadata, these users can find out which ETL job or the process can be used to load data into the given attribute. Like the control tables in the data warehouse, the operational metadata can be combined with the integrated metadata. For the end-users, it can be very powerful information availed at their fingertips. The result of metadata management may come up as another database consisting of the organization’s key attributes.
How does metadata management work?
Metadata management is among many such initiatives for a comprehensive data governance program, but it is the initiative that deals with metadata. Like MDM (Master Data Management) and DQ (Data Quality), the other initiates deal with the real data stored in the DBMS. We will discuss these in detail in other articles in the Database Administration 101 series. Here, metadata management can integrate the metadata stores at an enterprise level.
There are many tools like the Talend Metadata Manager, which helps automate load parsing of various metadata types. These tools also enable an enterprise model based on metadata derived from various systems as data integration tools, data warehouse, data modeling tools, etc. You need to know your specific requirements to know which will work best for your requirements. Thus you can select an appropriate one without any issues.
The users may further resolve any conflicts based on the names and types of sample attributes. It is also possible to create some custom metadata types with which you can stitch the metadata between different systems. A full-fledged metadata management system will give you a 360-degree view of all organization systems and how they are connected. This can be an ideal starting point for data governance initiatives. Data modelers can have all these in one place and look into different attributes. This governance model also can act as the foundation of the database, which we already talked about. Like any other such governance initiatives, individual metadata systems may keep on changing, but this model has to be updated following the SDLC methodology.
The purpose of metadata management
The fundamental objective to manage metadata is trust. Suppose there is no metadata management during the system lifecycle. In that case, there may be the creation of silos of inconsistent metadata, which may not meet any needs and may also put forth some conflicting information. The users may also be uncertain about how much they can trust the data if there is no metadata indicating the specifications of data as to how and when it got into the system and which business rules are applied. Take help from Remotedba.com to get the best results
You also need to consider the cost factor in terms of metadata management. Without managing metadata effectively, any development project cannot go through defining data requirements, which may further be decreasing efficiency. The users may be presented with many tools, which may, however, be creating redundancy and also will incur exceeding costs. With this, you may not be getting the best return on investment. Data definitions may be duplicated across different systems by incurring more storage costs.
As the business becomes more mature and more systems get added to it, there may be a need to consider further how metadata is effectively governed. Management of metadata offers many clear advantages to businesses and technical users, and organizations as a whole.
Top metadata management tools
Here are some of the top choices in metadata management tools.
- Alation Data Catalog
Alation is a comprehensive repository for enterprise data that offers a single point reference for the business glossaries, Wiki articles, data dictionaries, etc. This metadata management tool also offers a better insight into how the users create and share their information.
- Alex Solutions
Alex Solutions features the business glossary, which will enable the users to custom define and maintain the business terms and then link those to the actual data assets and processes. Policy-driven data quality will help combine the data lineage with data profiling and intelligent tagging based on machine learning. It also features intelligent tagging, which helps users add business context to the data assets and make integrations simpler.
- ASG Enterprise Data Intelligence
ASG offers a comprehensive data intelligence platform that can discover data from many traditional big data sources. These tools feature automated data tagging using pattern matching, reference data integration, and enhanced metrics. The automated business linage will let the users understand the data better and enhance the governance capabilities by tracing data from the traditional sources and the data lakes. AST’s EDI product offers a highly impressive portfolio, including vendor support and customers touting for various use cases.
Other metadata management tools include Collibra Catalog and Collibra Privacy & Risk, Erwin EDGE, IBM InfoSphere, Infogix Data360 Govern, Informatica Metadata Manager, Octopi, Oracle Enterprise Metadata Management, SAP PowerDesigner, Smartlogic Semaphore, etc.