How to start the implementation of InfoSphere Business Glossary

InfoSphere Business Glossary (IBG or BG) is a very useful "Data Concept Management Tool" to connect all users of data at an enterprise. BG is part of the IBM Information Server tool suite and is intended to be used as a enterprise glossary of business concepts and terms. With the metadata interchange support and the Information Server Metadata Server, a business term described in BG can be connected to a technical asset such as a column in a table, an ETL job that populates a table, a field member of a Business Intelligence report, or flat file contained in a delivery between enterprise applications. Another key feature of BG is the use of data steward. A data steward (person, role or group) can be assigned as an owner of a business term defined in BG. This provides an opportunity of creating an enterprise data governance structure. The ownership concept provides an enterprise-wide awareness of data and quality of data.
 
Implementation of BG normally requires a team of allocated resources (e.g., a project team or a task force) to start an initial "enabling" phase to define the work process and to actually implement a substantial amount of key business terms and concepts. The following is a list of key issues or topics that such team must work with in order to create a successful initial implementation of Business Glossary.

1. Creating a data owner/steward role in the enterprise
    Apparently, making terms without knowing if it is correct or wrong does not make any sense at all. The enterprise must have employees that care and use the data that a term describes. Designing a role like data steward will not cost the employee a huge amount of extra working hours. On the long term perspective, the data owner can guardian the data and quality of data which will, in return, helps the enterprise to make the right business decisions based on the reports/dashboards/mining results that are based on the data.

2. Designing a basic category structure in BG
   Business Glossary is a very simple tool. All business terms are located in categories. All categories are having a tree structure. A term physically located in one category can be "referred" by another category. A term can be connected to other terms as synonyms.
   Generally, a good structure in BG contains top categories that classifies the business concepts. For example, there can be a category called "Customer" which includes all kinds of business terms and concepts regarding customers to this enterprise. If all the top categories in BG are about such kind of major business conceptual areas, for example, "Customer," "Branch," "Product," "Agreements," etc., any users in the enterprise will find it not difficult to browse around to understand all the key business areas and business concepts. Besides, the search functionality in BG is well enough for any newcomers to look around.

3. Designing the work processes around BG
    Typically, when users start to use BG, there will be requirements on how to let data steward edit the terms, how to manage the life cycle of terms (in BG, a term can be "standard," "accepted," "candidate," or "deprecated"), and how to make sure that all contents are having back-ups etc. There can be many more such questions to the maintenance team of the BG content.
    In addition, when BG is used and maintained in a strict enterprise environment where there can be TEST, FREEZE and PRODUCTION instances, the work processes seem to be more important.

4. Marketing and making organizational implementation
    A tool like Business Glossary does not contain any fancy and complicated functionality such that all users of the enterprise can suddenly start enjoying and cheering up every time they find it useful. The team must go out and communicate with almost everyone in the enterprise in order to have a good start on the tool. Here, the data stewards team should be the first group that get familiar (and enjoyable) with the tool and start (with their charms) to influence other enterprise users as "Business Glossary advocates" until everybody likes it.

5. Starting populating the terms
    Normally an enterprise must have several key business concepts that are used throughout almost all activities/documentations, such as customer, internal units, employee, etc. It is very unlikely that one cannot find any employee that cares about terms and concepts in these core conceptual areas. In other words, one should find it possible and possibly easy to define and describe terms and assign data stewards in these core concepts. Giving a dedicated period and resource to populate terms in such core business conceptual areas gives a huge positive impact on the success of Business Glossary.

The concept of having a Business Glossary is to use the "crown sourcing" power to improve and align the organization on the data and information usage. It paves the way for successful business intelligence implementation in the long run. Hopefully, we could expect more social and collaborative features from Business Glossary in the future.

Reading notes for "Universal Metadata Models" Part I

This is the second book by David Marco on metadata management in large enterprises. Michael Jennings is the second author of this book.



Part I, Presenting the Managed Metadata Environment

First, a managed metadata environment (MME) is far from being just a repository of metadata or a data warehouse. Building a data warehouse for metadata is much more difficult than a data warehouse for normal data because of the various data sources and the difficulty of maintaining the link among the data.

There are companies trying to do point-to-point integration with EAI tools or just using XML. What can be problematic with such approaches is that, when the company grows too large, the effort to maintaining the integration will very easily over the whole IT budget. So, it’s better to start thinking of building an MME as early as you can.

It’s quite inevitable that, when thinking of building MME from an architectural point of view, there are architecture elements that are much similar to what data warehouse architecture includes. Specifically, they are, sourcing layer, integration layer, repository, data management layer, data marts, and data delivery layer.

Similar to the development of a data warehouse, the governance and stewardship models of metadata are also important.


What can we achieve when we have a good MME? If we look at the SE-CMM for data warehousing (CMM is always something big enterprise is focused on and it indeed can help these enterprises to improve the business by reducing cost and promoting new business opportunities), most global 2000 companies are at levels 1 or 2. By having a good MME, it is possible to move up to level 3 and level 4 (it’s called “world class”). And of course, level 5 (continuously improving) has never been achieved by anyone yet.