As technology continues to reshape the business landscape and intensify competition, many businesses have turned to hybrid – or even multi – cloud deployment as a way of keeping up with innovation and staying agile in today’s saturated marketplace. The benefits of this shift in strategy are obvious – cloud technologies offer an array of opportunities that were not previously possible; from enabling unlimited scalability at lower costs, to facilitating rapid service delivery by improving the efficiency of internal infrastructures.
Yet, for all the benefits that the cloud has to offer, stakeholders can jump the gun in deploying their cloud strategies; often entirely overlooking the data that is actually housed in the cloud. This can lead to bigger challenges later down the line, particularly for the various business units who all have competing needs and must upload, access, and analyse different types of data. As the volume of data continues to multiply at an exponential rate – and will inevitably challenge a one-dimensional cloud strategy – integrating proper data management is the key to empowering organisations to stay agile and maintain an unbeatable competitive advantage.
With time of the essence in today’s fast-evolving market, organisations must understand how interconnected data and cloud strategies are to a building a cohesive and successful business strategy. Given the multi-faceted requirements of different business functions, it is critical for enterprises to understand how they can adapt their cloud strategies and integrate data management to serve the three key personas in cloud deployment, all of whom will play central roles in driving growth.
The IT Decision Maker
More often than not, the two key focus areas of the IT decision maker are cost savings and operational efficiency. Cloud technologies offer huge, interconnected benefits for both aspects – for example, it helps reduce spending on data centres and hardware, in turn freeing up more capital to be reallocated to new business opportunities and other growth initiatives.
Despite all its potential, however, some decision makers are finding that their hybrid or multi-cloud deployments are actually creating more challenges than opportunities. As the volume of data continues to rise, regulatory compliance requirements multiply, and external vendor partnerships pose new risks, these new factors are racking up unmanageable and unanticipated costs. This has led to some organisations to move their data facilities back on-prem, leaving their initial investments in the cloud to go to waste.
A solid, comprehensive data management solution can help IT decision makers effectively determine and anticipate current and future cloud deployment costs. By implementing a set of strong data management principles and best practices, IT decision makers can classify and contextualise their vast repository of data and gain a single, 360-degree view of their enterprise. This allows them to evaluate the types of workloads that work best on the cloud, and the kinds of workloads that work better on-prem; thereby facilitating cost-productivity comparisons and preventing wasted capital on inefficient cloud deployments.
The Developer
Central to a developer’s role is the ability to continuously develop, test, and deliver high-quality applications in a rapid and agile manner. However, with the recent proliferation of cloud services such as hybrid cloud, developers are now faced with the time-consuming inefficiency of having to rewrite and re-upload the same code several times for different cloud vendors; causing backlogs in their everyday workloads.
Modern data management solutions often provide containerisation facilities, which allow developers to bundle an application and all its libraries, files, and code into one package. In doing so, the challenge of having to cater to various cloud vendors is eliminated as developers can simply write their code once and instantly deploy it to multiple clouds. The key benefit here is flexibility: developers can transition and move applications, data, and workloads not only between on-prem and cloud platforms, but also between various cloud platforms themselves. This, of course, presents significant competitive advantages in easing developers’ workloads and helping them become more efficient, agile, and productive.
Containerising apps also helps mitigate the issue of ‘vendor lock-in’ that tends to arise with native cloud apps. Once developers write code for a certain cloud vendor and upload all their data and apps onto the system, the process of switching to- or adding- another cloud vendor becomes a very expensive and difficult process. In its ability to support multiple clouds, however, containerisation prevents developers from being chained to a single cloud vendor, whilst simultaneously helping the IT decision maker leverage arbitrage between different vendors and ensure the right level of associated costs.
The Big Data Operator
Last, but certainly not least, is the big data operator. To keep up with the fast pace of today’s competitive market, big data operators need a data management solution that provides them with a high level of self-service and instant access to the right analytics tools to avoid cloud deployment.
Without these, big data operators will find that the information they need is scattered across multiple clouds and on-prem. They are forced to spend hours wading through the murky depths of unclassified data, leading to imminent setbacks in productivity and service delivery.
A modern data management platform that offers point solutions will allow big data operators to instantly spin up their desired workload on any cloud for any specific use case. These types of on demand data tools enables them to quickly move from one task to another and ultimately improve their efficiency to avoid cloud deployment.
Furthermore, robust data management also provides big data operators with a single source of truth that can be applied to stacks running both on-prem and in various clouds. With the GDPR now in effect, implementing a strong, single set of security and data governance policies for all systems is key to not only staying compliant, but also avoiding the huge overhead costs that result from writing multiple copies for each platform.
Capitalising on the potential of cloud technology requires more than its isolated adoption. To maintain a forward-thinking business model that maximises the benefits of the cloud, organisations must first anticipate and serve the needs of its key stakeholders through robust data management. With these strong data practices in place, only then can cloud deployments successfully take off and empower digital transformation across the business.
Joe Morrissey has built International sales organisations for three of the most successful Open Source Enterprise Software companies globally: MySQL (Acquired for $1b by SUN -2008), MongoDB (IPO:MDB 2017) and Hortonworks ( IPO:HDP 2014)