Connecting the Dots: An Introduction

Connecting the Dots: An Introduction

A new series of posts by Rick Sherman who writes:

In the real world the situations I discuss or encounter in enterprise BI, data warehousing and MDM implementations lead me to the conclusion that many enterprises simply do not connect the dots. These implementations potentially involve various disciplines such as data modeling, business and data requirements gathering, data profiling, data integration, data architecture, technical architecture, BI design, data governance, master data management (MDM) and predictive analytics. Although many BI project teams have experience in each of these disciplines they’re not applying the knowledge from one discipline to another.

The result is knowledge silos where the the best practices and experience from one discipline is not applied in the other disciplines.

The impact is a loss in productivity for all, higher long-term costs and poorly constructed solutions. This often results in solutions that are difficult to change as the business changes, don’t scale as the data volumes or numbers of uses increase, or is costly to maintain and operate.

Imagine that, knowledge silos in the practice of eliminating knowledge silos.

I suspect that reflects the reality that each of us is a model of a knowledge silo. There are areas we like better than others, areas we know better than others, areas where we simply don’t have the time to learn. But when asked for an answer to our part of a project, we have to have some answer, so we give the one we know. Hard to imagine us doing otherwise.

We can try to offset that natural tendency by reading broadly, looking for new areas or opportunities to learn new techniques, or at least have team members or consultants who make a practice out of surveying knowledge techniques broadly.

Rick promises to show how data modeling is disconnected from the other BI disciplines in the next Connecting the Dots post.

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