Filed under: Data Governance, information strategy, Recommendations
Data governance is a practice for ensuring that policies about information acquisition, use, protection, and disposition are defined, approved, and importantly, observed across the organization. Information policies are defined in relation to business policies and must be aligned with the corporate mission. Read more
Filed under: Business Intelligence, Business Rules, Recommendations, Replication
In my last post, we looked at some common use cases for operational synchronization, and each of those examples were effectively abstractions of scenarios in which there is benefit in establishing consistency and currency among either logically or physically distinct data assets. For example, creating a holistic and complete view of shared data entities is critical to any distributed master data management repository or distributed identity management service. Read more
Filed under: Business Intelligence, Data Analysis, Data Integration, Metadata, Recommendations, Replication
Over time, organizations have employed a variety of strategies for managing data assets in accordance with the specific needs of the different business applications in operation. For the most part, applications were designed to achieve specific objectives within each business function. Correspondingly, any data necessary for the business function would be managed locally, while any data deemed critical to the organization would be subsumed into a centralized repository.
Yet this approach to centralizing data has come under scrutiny. Read more
This is a repost of an article I wrote back in 1999, but I thought it might be interesting to recycle it, since it still seems relevant. I did edit it a little – I wrote it after the birth of my second child, who is now 11, so it did not make sense to refer to him as a baby ;-). Here it is:
A null value is a missing value. Yet a value that is “not there” may provide more information than one might think, because there may be different reasons that the value might be missing. A null value might actually represent an unavailable value, that the attribute is not applicable for this entity, that there is no value in the attribute’s domain that correctly classifies this entity, etc. Or the value may actually be missing!
Filed under: Data Governance, Metadata, Recommendations, Uncategorized
At the recent DGIQ (Data Governance and Information Quality) conference, I had the opportunity to chat with Ian Rowlands, Senior Director of Strategy at ASG about historical trends in computing. In particular, we discussed how concepts such as centralization and distribution have come into and then out of vogue, as I pointed out that the new trend towards the “cloud” was essentially a re-boot of the old concept of time sharing on a mainframe.