The importance of identifying and addressing the root cause of a data quality issue should never be overlooked. In this series of articles I will cover the most important techniques which help you uncover the root cause. This week will focus on the 5 whys, root cause analysis technique. Definition Iterative interrogative technique to determine the …read more

Any fundraising shop would have some data on foundations and other charitable organizations who made a gift in the past, are a future prospect, etc. Depending on how many charities you have in your database and how many new ones you are bringing, it can become cumbersome to keep track of: Their status as a …read more

Big Data in healthcare offers a new direction to the current medical models. Especially when it is accompanied with cloud computing, the efficiency of Big Data amplifies. Thanks to Big Data and its boosted utilization, there seems to be a tremendous increase in profit. It is because of the better business intelligence. However, more profit …read more

As part of a sustainable data quality program, you need to identify the issues of your bad data. Otherwise you will keep spinning your wheels and using your resources to constantly correct the issue, but never addressing the cause(s). There are many data quality root cause analysis techniques you can use and I will start …read more

One of the challenges for starting a data governance program is a lack of funding. Luckily for us, there are 3 proven ways to secure funding for a data governance program. More details in the video below: 1. Business case A strong start of a program is to put together a business case for it. …read more

I know it’s not easy to put the necessary foundation in place for a successful data governance program, not to even mention the data governance artifacts / deliverables. On the foundation piece, I’m referring to the: initial business case the data governance operational framework maturity model the data governance council guiding principles resources, etc. Let’s …read more

I feel that for the past few years Data Analytics and Business Analytics have turned into those buzzwords which everyone is using, but with different meanings. Not to mention the never ending questions and debates on: “How is Business Intelligence (BI) different from Data/ Business Analytics?”, “Is Data Analytics a function of BI?”, “Is BI …read more

Maturity models contain a set of levels or phases, each with their own characteristics, usually about the status of processes and structures, people and culture, tools technology.  As an organization advances in a level/ phase, it is considered more mature in its treatment, usage, and understanding towards data and information. Organizations often use maturity models as a …read more

A lot of times report developers are working against a running clock to deliver the reports they are asked to produce as quickly as possible. As such, many times we end up with a multitude of reports with different looks and feels as this is usually a lower priority. Best practices ask for a consistency in …read more

Participating as a speaker at different international conferences and being engaged in different data governance communities, provides me with a lot of interactions with data professionals from different industries, countries, and organizational cultures. I’m always interested to know how each organization develops and evolves its data governance program, how it structures its operating model, and …read more