When you’re setting up a data stewardship program, you need to start thinking of not only who to assign as data stewards and the operational framework, but also who the data stewards should report to, from a data governance organization perspective. The role of the data steward is usually not a new position that is …read more

Effective Data Warehoues (DW) data source profiling is often an overlooked step in data warehouse data preparation. DW project teams need to understand all quality aspects of source data before preparation for downstream consumption. Beyond simple visual examination, you need to profile, visualize, detect outliers, and find null values and other junk data in your …read more

This quick guide provides an overview of the basic concepts in fault tree analysis technique, as it applies to data quality. For some more well-known and useful root cause analysis techniques, please check out the: 5 whys analysis Fishbone diagram Barrier analysis Pareto analysis Definition The fault tree analysis is a top-down, deductive failure analysis …read more

In the competitive world today, clearly defining and understanding business terms is the first step to guaranteed success. Incorrect interpretation is causing misunderstandings and increase the risk of having bad information and bad decisions. These, in turn, lead to expensive operational, marketing, sales, procurement mistakes and so on. When employees misinterpret business terms, like when …read more

As most of us already know, the data governance sponsor plays a critical role in the success of a data governance program. Without sponsorship at an executive level, data governance programs often lack the funding and resources required to get off the ground. They simply remain at the initiative level or in a best case …read more

If I could give some advice for all colleagues who are about to start a data governance project, I would say: Speak up! In my professional career I have seen countless projects fail because leaders didn’t know how to manage communication and expectations. My objective here is to explain how communication practices can save (or …read more

Data warehousing for business intelligence and “big data initiatives” continues to gain significance as organizations become more aware of the benefits of decision oriented data warehouses. However, a key issue, with the rapid development and implementation of data warehouses, is that data quality defects are often injected during the multiple lifecycle stages of the warehouse. …read more

Project Managers have a very structured way of conducting activities. This skill is very helpful when managing data governance projects and your intention is to add more value to the expected deliverables, keeping everything else on track. When I was a hired by xMatters I was given a very specific mission: ISO 27001 certification by …read more

I’ve previously wrote about more obscure, though intriguing, data roles I’ve encountered, but I’ve been asked several times to go over the main data roles found in a data governance program. I’ll skip the sometimes dreaded introduction and get straight to it. The 5 main data roles found in data governance programs are: 1. Data …read more

To get a successful business intelligence (BI) program started, I believe it should aim to address and abide by the following 6 goals: 1. Information must be easily accessible End users must be able to access information in a timely fashion so that their timely decision making is not compromised by this. Ease of accessibility …read more