Future Proofing Solutions - What are we looking for in Hybrid Cloud Analytics?

Sharryn Napier, VP & Regional Director, Qlik (Australia And New Zealand))

Sharryn Napier, VP & Regional Director, Qlik (Australia And New Zealand))

Recently, we have seen a move towards “hybrid” – hybrid vehicles, hybrid sports equipment, and more latterly hybrid watches. And why wouldn’t we? A hybrid approach brings with it the best of both worlds with resounding benefits to the end users, including increased capabilities and reduced costs.

In the business world, we are increasingly seeing “hybrid cloud environments”, which use a combination of on-premise, private, and/or public cloud infrastructure to deliver services in a computing environment.

It is therefore vital to gain a deeper understanding of what exactly hybrid cloud analytics is, including its essential components and considerations for businesses. While many vendors will claim “hybrid cloud analytics” in their marketing verbiage, you have to get into a little more of the details to better comprehend what value you are getting. For instance, being able to publish an analytical application (or sheet for some) from an on-premise installation to a cloud offering could be beneficial, but it’s not hybrid cloud analytics. There are a few crucial ingredients that we use to define our approach for hybrid cloud analytics:

1. Transparency – Firstly, a hybrid cloud analytics solution should be completely transparent to the end users with regard to where the data resides, and where the analysis happens.

Any user should be able to access their environment, from any device, and choose what data and/or applications they want to view and interact with, regardless of where it sits and runs. You should have universal hub which represents everything available to a user based on their role and security permissions, not the location of where things reside and run.

2. Location enforcement – For many reasons, users may choose a particular data source, therefore the analysis that is run against that data should stay in its particular environment. Typically, it is about restricting data and/or the analytical applications with that data to an onsite environment, behind firewalls and other safety mechanisms. This may be due to several reasons but not limited to industry regulations or data that represents a company’s most secret competitive weapon. Regardless, a properly governed solution enables organisations to define rules around where data and/or the analysis on that data can be stored or run. For example, a company might deem a particular data source too sensitive to be allowed outside of the firewall, and that any analytical application that uses the data source should therefore run behind the firewall. By simply designating this in a management console, users can create enforcement rules on where things can and will reside based on that dataset.

3. Orchestrated entitlement and bi-directional migration – One obvious need is for organisations to be able to easily manage entitlements and licensing for their user base across the hybrid cloud solution. This is a basic element of “orchestration between the platforms” and is essential to delivering hybrid cloud analytics. At the same time, if the whole point is to enable customers to choose where data and analysis should occur, based on their own criteria, then hybrid cloud analytics must allow for bi-directional migration to/from one infrastructure environment to another in the hybrid cloud deployment.

4. Single management console – A hybrid cloud analytical solution should be managed as one, seamless environment across infrastructure boundaries, so it should be managed via a single console. Period.

Hybrid cloud analytics is here and its potential is obvious. However, in order to derive valuable business insights from the data that lies in hybrid cloud infrastructures, businesses need to understand the true meaning of hybrid cloud analytics to make full use of the technology.