See things clearly

Thought I would share some thoughts...I recently came across OBASHI Methodology after researching for appropriate Enterprise Architecture diagram / notation methods in relation to Data Governance. 

I have found that the ability to dynamically join the dots between the Business and IT assets enables Data Governance to visualise the Data Map of a company.

The mapping of Data Flows certainly provided possibilities for layers of Data Types for Organisational Mapping ie Personal Data, Sensitive Personal Data by Data Controllers. 

Data Owners were also mapped to the Ownership layer alongside the Business Process using the Personal Data as an asset.

Interested to hear of any Data Governance perspectives..

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I thought, before drafting a reply, I would look at a few definitions of Data Governance and I found these:

"Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise."


"A quality control discipline that encompasses the people, processes and information technology to create consistent and proper handling of data."

Data Quality Network 

"Data Governance encompasses the people, processes, and information technology required to create consistent and proper handling of data and understanding of information across the organisation, ignoring the boundaries created by organisational structures."

Alan, Duncan, Research Director for Business Analytics, Gartner Inc

"We believe that organizations that are able to embed disciplined Data Governance which encompasses the people, processes, architecture, tools and technology required to deliver their data consumption and usage requirements will be successful."

Expert Insight - Delivering business value through robust data governance,



The common thread running through these definitions is the interaction between people, process and technology which must be understood in order to provide a context under which good data governance can occur. 

OBASHI has been designed to create clarity on exactly that – the interactions of people, process and technology - in a way that is simple to understand and communicate with others.


In order to manage risk; understand the quality of data required; put effective policies in place; and be able to quantify the effect of changing business processes, we need to understand how data is created, how it is used, any manipulation which takes place to it, and the decisions which are made dependant on it.


As I wrote in 2012 in the article "OBASHI and data governance",


"Understanding where data comes from, which assets it passes through, and the business processes it feeds, are critical to understanding the required level of data quality, how data should be managed, and the risk of data "errors" to the business."


While OBASHI doesn't deal with the specific content of the data, it does provide a framework on which we can make decisions regarding the robustness and levels of quality required by the data.  


It might be worth taking a look at another article on OBASHI Think, "Data Quality and Formula 1" which explores the question of data quality in a more detail.  Although we can't say too much about it, OBASHI diagrams were used trackside at every Formula 1 race last season.  We've a Case Study you can read here which details some of the benefits its use brought within one particular F1 team.


When it comes to Data Governance Policy documentation, the addition of B&IT diagrams and Dataflow Analysis Views is a great way of documenting and auditing why policy decisions have been made and the assets those policies must cover.


Hope the above helps,




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