Information Excellence – Metadata Management

Information Excellence for Digital Business: Metadata Management

In my previous blog I discussed at a high level three aspects of Information Excellence for Digital Business; Transforming Data into Insight, Acting in the Moment, and Innovating without Constraints.

While the business drivers for information excellence may not be surprising;

• Business innovation
• Improved decision making
• Increased efficiency and agility
• Greater compliance and risk management

I think the breadth of capabilities need to achieve information excellence may surprise some.

Consequently, I decided for 2017 I will do a blog series on how different enterprise information management capabilities support information excellence. Although I will writing about specific capabilities it is important to remember that they need to work together holistically to achieve the desired outcomes. Metadata management a core component of enterprise architecture is the focus of this blog. And according to IDC, enterprise architecture is at the heart of an organization’s ability to execute digital transformation.

Now let me start by saying I’m no expert, and for some I may over simplify things. You can find resources from people much smarter than me on the SAP Community Network for Enterprise Architecture. I also want to be clear that I don’t just mean technical metadata about database tables and fields, I also include things such as business semantics, what processes and systems use the data and content (documents, images, videos, etc), APIs and business rules that control the flow of information, and policies that classify and govern the information.

Transforming Data into Insight – Metadata makes data and content findable and understandable by a person, computer system, or IoT device. Metadata discovery capabilities can analyze different sources and build a catalog of information assets, as well as a semantic knowledge graph that helps in understanding relationships between information entities and attributes.

Metadata can document the lineage, and frequency of update of data flowing into a data lake, as well as business terms, usage statistics, security classification, and privacy requirements that can help people determine if a data set is appropriate for use in the context of their analysis. And machine learning can use the metadata to recommend related data/content sets based on criteria such as domain (customer, supplier, material, asset, etc), location, business process, and algorithm being used, as well as suggest how to best model structured, semi-structured and unstructured information for analysis. The result of all of this being broader and deeper insights to help drive desired business outcomes.

For example, TUI is using metadata and machine learning to automatically classify and cluster social media posts to gain insights that drive better customer engagement and satisfaction.

Acting in the Moment – Metadata management helps facilitate seamless exchange of information across distributed cloud and on-premise applications, as well as IoT devices. This is done by cataloging business definitions of data entities and attributes in order to create a mediation layer that ensures the semantics of data can be reconciled across systems and devices. Machine learning algorithms can also analyze standard definitions, existing mappings and metadata such as industry, location, and business process to define models and attributes, optimal interfaces and mapping guidelines for cross enterprise process orchestration.

For example, metadata helps the City of Buenos Aires, match information from citywide sensors, citizen social media posts, work plans and maintenance schedules so they can monitor and fix infrastructure issues in real-time.

Innovating without Constraints – Metadata plays an important function in the development, provisioning, and use of mobile applications. This includes UIs, data bindings, screen transitions and actions when a user interacts with the device controls, as well as configuration, content type definitions, authentication and authorization, and integration with back end systems.

For example, Adarsh, India’s largest credit co-operative empowers its 100,000 agent advisors to better service its million plus members — including those in the most remote areas — all from a basic feature phone.

I would love to hear your thoughts and examples of the importance of metadata for digital business.