Three terms that have been well used over the last several years, but that are frequently misunderstood.
How can we be having record cold temperatures and storms on (for example) the United States East coast? The planet is getting colder, not warmer.
Global warming is one of those names that, whilst technically accurate (the planet is getting warmer) seems inaccurate based on local conditions.
When a warmer ocean translates to colder winters on the East coast the science conflicts with people’s reality.
The reality is that the climate is changing – in some areas (such as the Southern Cape of South Africa) getting hotter and drier, and in others becoming colder or wetter. Bigger hurricanes, and bigger droughts.
If we used the term “climate change” instead of “global warming” this would leave less room for nay saying.
Similarly, two commonly used data management terms create similar confusion.
A common misconception created by the term bug data is that it must be terabytes or zettabytes in size.
In fact, big data can be more accurately described as complex data. Data that is complex in more than one way – whether through a combination of size (volume) and shape (variety), or volume and the rate of change (velocity) Or velocity and variety.
A large set of differently shaped data sets (of relatively low volume) that are being updated multiple times per second and must be analysed for insights is big data – even though the size may only be gigabyte or even megabytes.
Big data is about getting insights from complex data sets – not about size.
Last, but certainly not least, data governance.
Talk data governance to most people and you conjure pictures of long, fruitless meetings arguing about the definitions of terms – aka “what is the meaning of customer”
In many cases, data governance is confused with other data management capabilities, such as (in the example stated) metadata management.
In fact, data governance is not about governing data at all. Data governance is about driving the behaviour you want in your business in order to ensure trusted data.
Data governance is people governance. It is a change process that lays the foundation for advanced analytics, compliance and everything else.
For example, in order to deliver customer insights we may want to ensure that:
- We are working with the most recent source of customer data – a behaviour
- We bring in demographics data that suit our intended outcome – a behaviour
- That our data is of sufficient quality – a behaviour
- and so on.
Data governance is the process that defines these behaviours – how do we identify the most recent source of customer data, what demographics data do we need and where do we source it, what does “sufficient quality” look like and how do we ensure that data meets this requirement, and so on.
Most of us are doing data governance every day – we are working with data and making decisions and taking actions based on our immediate requirements or project.
Formalising data governance elevates these actions to a group level to ensure that actions taken and decisions made serve the greater goals and priorities of the overall business.