Organisations with aspirations to increase their footprint in the Cloud will need to start by revising their Data Governance and Data
Management policies. Not something that is new to many, but you will need to modify what you have. Data Management and
Governance are the keystone policies which underpin the services levels, ownership and processes that determine not only the
lifecycle, activity and location of the data assets but also factors such as accessibility, consistency, accuracy, protection, performance
and security. Beyond this, factors that determine the archival and backup requirements of the data, who has access, what the audit
procedure looks like and finally how compliance and regulation impacts on data assets in the Cloud need well defined policies and rules.
One thing is certain, moving to cloud will amplify Data Governance and Management challenges and while this activity may be perceived
as a technical activity, it is not. Data is an institutional resource and as such the responsibility and accountability falls firmly within the
realm of Business Process Governance. However it is correct to say that compliance with data governance and management policy will
certainly be achieved through technology, but technology definitely isn’t the starting point.
Any good data governance and management plan will follow the data regardless of location, application, server platform, Network or
storage. It must be both adaptable and enforceable wherever the data resides, whatever cloud model has been adopted.Revisiting
and redefining the Data Governance and Management plan will also require a solid understanding of the impact of the supply and
demand profile on IT resources. The capacity and performance requirements profile will indicate the elasticity required to meet demand.
I am always reminded of the seasonal variation in demand on retail organisations. When holiday time comes around there is always a
significant spike in sales, fueling a subsequent demand in IT resources. In the past the capacity plan / forecast model would have
greatly influenced budgeting and the procurement requirements. For these organisations holiday time defines their yearly results,
success or failure. However, if capital invested to meet the seasonal peak demand is likely to provide a Return on Capital Employed
(ROCE) for 3 months of the year. For the remaining 9 months the ROCE calculation is likely to look bleak, indicating that the organisation
has not invested its capital effectively.
A better model may be based on cloud where the IT demand determined from the retail peak 3 months is satisfied by elastically
expanding into the cloud and once the peak is past, contracting back. The ROCE calculation, and the shareholder value, looks much
more effective if based on the capacity / performance plan from the 9 months of the retail year where the profile is more uniform.
Of course retail is only one example. There are many others where the peak demand occurs at a greater or lesser frequency. However,
the concept of buying IT resources and services when you need them to meet peak demand and giving them back when you’re finished
is a very attractive one.
There is no doubt that the Data Governance and Management plan will always be a ‘Work in Progress’, at some point you will arrive at
the version of the plan that consists of a number of mandatory and desirable requirements. One key activity will be to baseline your
operation. This gives you the insight you need to plan, forecast and carry out the ‘What If’ analysis.
We have certainly reached the point where the Compute and Networking elements have become more ephemeral in nature, mainly
due to virtualisation. They can be easily moved, rerouted, stopped and started without causing application disruption. Whereas
data is more challenging to manage and move. It has mass, it’s heavy and any activity is typically restricted by compliance and audit rules.
To summarise the challenges I have discussed here, it is clear that in this dynamic new age of IT flexibility, choice, risk and cost remain the
keywords that influence competitive success. As I said earlier, technology is not the starting point, however when you arrive at an agreed
Data Governance and Management model it will be time to look at the technologies that drive the best flexibility, Choice, Risk and cost. It
is these metrics that define your Data Fabric and enable a consistent data format, software defined data management and fast efficient
Whether it ‘s on premise, off premise, in or near Hyperscaler cloud I do not want the cost and inflexibility of doing the same thing multiple
different ways. I need to be able to move data rapidly both into and out of the cloud. I need different performance for different types of
work, and I need to be able to move between these performance tiers with ease. These are just a handful of the data governance
challenges that NetApp Data ONTAP help you meet your mandatory requirements with ease.
Finally, there is an excellent whitepaper I recommend to you which discusses the Importance of Data Control in Hybrid IT.
You will find it here : The importance of Data Control in Hybrid IT