In this posting we will continue to discuss metadata management, taking a little deeper look at metadata and examining some of the challenges of successful metadata management.
Consider the following questions: How do you ensure that you are exploiting the metadata you are collecting to the fullest, possible extent? How do you make sure that your metadata is easily accessible and effectively used across your organization? How do you ensure that it is kept up-to-date so that new metadata about new data is incorporated? A few areas of focus help to meet the challenges of managing metadata, and address these questions.
Disparate information sources
The first challenge to leveraging your information is the wide variety of sources that make up the corporate data landscape. There is no escaping the fact that a significant portion of every organization’s vital data resides outside of its databases. In order to use metadata effectively, data managers must create a consistent and easy-to-understand format across everything from sophisticated, high-level ETL and BI repositories, down to rudimentary flat files.
Enforcing business rules for metadata
Creating a context of enforceable business rules around the metadata is an important aspect of maintaining data integrity and usability. While most repositories do an excellent job of collecting the metadata, they only provide a two-dimensional view; that is, they can help you understand the data lineage and attributes, but they do not help you understand the relationships around the data, a key piece of clarifying the dependencies associated with the data. For example, a bank would want to ensure that any time an “account” entity were created it would have to have an account type — such as “asset,” “liability,” or “equity” associated with it.
Data architects and DBAs must effectively communicate with all of the internal stakeholders who have access to, or are using data. As is evidenced in many different instances, if information about how to use data is hard to find or hard to use, it is likely that the data will be either misused or replicated with different standards and in a different format. Out-of-control application growth is at the root of data redundancy and inaccuracy. For this reason, clear communication is vital to leveraging metadata.
Hmmmm…These are indeed significant challenges. But as data management professionals we must continue to push to enable more flexible IT organizations. Doing so is the only way to ensure that we meet business needs, even in the face of explosive data growth. And metadata coupled with data modeling provides an important piece of the puzzle.
Increased visibility into corporate data landscapes helps organizations lower costs, ensure data integrity, and re-use existing data assets. Data architects and managers should make sure that any system that they put in place is dynamic enough to continually incorporate changes, and accessible enough to work across the breadth of stakeholders.
To achieve success requires planning, architecture, and strategy. We’ll talk more about these and other aspects of data management, metadata management, and administration in future postings. And please, feel free to sign in and share your thoughts with us in the space provided below.