Why is Metadata Management Important?

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As data types and quantity continues to increase, data management is becoming more and more important. Among the vast amount of data, we need to utilize the right data at a right time. This is where metadata management comes in. Metadata management(MDM) does more than just information governance. It enhances the data’s accessibility and credibility which leads to analytics consistency. Find out how MDM makes searching, understanding the data easier and how it impacts analytics as well.

What is Metadata?

Metadata, in a literal sense, is data that describes the data. In a broader sense, it is data created along the contents of the data asset for efficient search, based on a specific rule. So as a general, metadata is structured (information) data which makes the data easier to understand and leads to efficient communication.

There are two fields of governance:

1) Analytics governance

Data Valuation

Improving the quality of data by semantic data management, data modeling and valuation of applied data

Data Analysis

Getting insights from data with discovery data, catalogs, workflow management

2) Information governance

Data Governance

Moving and transforming or data, authentication or audit, data enrichment, data life cycle or lineage management

Data Risk and Compliance

Protecting data at rest or active, data compliance

MDM with Analytics: Better Analysis, Better Insights

Case of separated information governance and analytics governance results as lack of utilization. After going through stages of original data source > creating data mart > analysis > visualization for a certain time, distance is seldom created between the selected data and the original data source. As changes in the data happen in the analysis stage, it becomes harder to keep in track from the original data source. This results in confusion and inconsistency which weakens analytics effectiveness.

Linking the two governance enables discovering new means of utilizing data sources. Metadata is the key in the linkage. It means that information and analytics should be governed together with the metadata of the data source used in each aspect. In many cases, people have started to implement data catalogs to overcome wrong application of analytics caused by untrusted data. Data catalog is enterprise metadata management.

The Metadata Management System works as a bridge between data and analytics governance programs. The below diagram will help understand how:

According to Gartner, linking the two governance types by using metadata improves business analytics in the following ways:

• Holding and managing data in a single logical instance, singly defined and managed
• Standardizing processes for managing data across and within markets, business units and geographies
• Improving regulatory compliance
• Embedding compliance and privacy (master data to augment risk management, customer care and compliance, as well as data protections)
• Reducing data and processing errors, lowering operational support costs and improving operational capabilities
• Enhancing analytics and reporting accuracy

Coming soon!

Metadata Management is coming soon in metatron discovery, so please be updated with us for more information!