Dispelling Common Myths About Cloud Computing

Cloud computing has truly grown into its skin in terms of its impact on the modern technological landscape. Most major industries now implement and rely on some form of cloud-based storage to improve their efficiency and niche-specific innovation. Still, even with the cloud’s growing maturity and agility, it still remains at the center of several myths stemming mainly from its security, financial constraints, and overall usability.

Here are logical responses to several cloud-based myths.

“The cloud is the end-all/be-all of success”

While cloud computing holds immense potential in terms of “speed-to-market” deliverables, it is not necessarily the only means of finding success in an increasingly data-driven business world. The best rule of thumb is to conduct an analysis of your company’s specific needs, goals, and weaknesses and determine if cloud-based software will stand as an asset to achieving and mending these matters. The reality is that there are several major breakthroughs going on in the business technology sector (virtualization, autonomy), and these innovations may simply serve your company in a more constructive manner.

In short, the cloud is great, but “cloud washing” is not.

“The cloud is unsafe”

A common concern surrounding the cloud stems from its security, and this notion is reasonable given the amount of precious data held within cloud communities. However, much of this skepticism is unfounded, as there have been very few public cloud security breaches since the concept took off as a technological norm.

The cloud is obviously not impenetrable, but its security is much stronger and more consistent than many commentators would lead you to believe.

“The cloud is typically not reflective of a company-wide decision”

Cloud computing is often given the false label of a “CEO-said-so” implementation — in other words it is perceived to be a change imposed on an entire company, regardless of majority interest. In reality, most companies make the switch to the cloud after a long planning and goal mapping process in which employees and executives alike weigh the pros and cons of such a move.

The cloud is almost never the result of a knee-jerk decision — its vast array of uses makes it almost impossible to be handled in such a way.

“Data shared in the cloud cannot be taken back”

Another reasonable, but mostly incorrect cloud-based fear comes from the stakes surrounding data storage. In many of these cases, the skeptic is under the impression that data stored in the cloud is essentially irrevocable. In the past, these beliefs were legitimate, but subsequent advances in data-based technology have given way to easier methods of data migration — both to and from the cloud.

Initial cloud-based data storage can be daunting, but rest assured that your data is far from “locked in.”

Adapting to Data as a CIO

The data revolution has put companies in an interesting position—swamped with information, it is now their responsibility to ascertain actionable insights as fast as possible to avoid falling behind. It’s a challenge to keep up—while there are plenty of tools for collecting big data, and plenty to analyze it as well, the sheer variety can overwhelm a CIO not prepared for the influx.

Because of this, data agility is king. Anyone can collect large amounts of data, but it takes a skill to translate this data into something that companies can take advantage of. Cloud platforms and databases such as Hadoop can help this effort in many ways, but it still falls to the CIO to track recent innovations and keep current. This in of itself requires a strong knowledge of data best practices; no company can adopt every new innovation, but picking and choosing the right scalable data infrastructure can ease the burden of adapting as time goes on.

A big part of a CIO’s responsibility to agile data is choosing a cloud platform that’s right for their business. Different individuals and stakeholders may have a diverse array of opinions on which is best. For instance, Google Cloud Platform may be preferred by a company’s data scientists for its machine learning capabilities, whereas the integration capability offered by Azure may be a good choice for developers. In cases like these, where a company will have to serve a variety of cloud users, it may be smart to consider a multicloud infrastructure to accommodate for as many needs as possible. This approach, though potentially more costly, can ensure that companies are able to harness the developments of each of these platforms in the future.

Beyond infrastructure, other tools exist to help a company maximize its data agility. Apache Drill is one such tool that circumvents the need for IT assistance to query data. It’s an SQL query engine that avoids the problems associated with schema creation while being ANSI SQL:2003 compliant. This and other tools like it are the key to gaining data insight as quickly as possible by cutting down on cycle time.

And concerns about data processing have changed over time. Before, hand coding data architecture was more common, and though it may still be serviceable for small, specialized projects, it is the antithesis to data agility in that it is time consuming to develop and always created for a specific platform. A better alternative for the modern business is data integration software, which takes the burden off of the business and supports new innovations and all types of cloud data.

That said, it takes a bit of vetting to choose the right integration software. The ideal software should be scalable, cross-platform, and allow for real-time data processing. It’s called an agile data fabric, and it’s meant to synthesize all types of data a company will need to work with. Platform agnosticism is important for the same reasons why a multicloud infrastructure is valuable; it allows the company to take advantage of new innovations and specific capabilities.

Organizations should also strive to be self-sufficient with their data. A controlled move to properly distributed data can greatly enhance insight. However, this requires a number of different participants within a company, including IT staff and dedicated data analysts, all with their own needs. A savvy CIO can craft an infrastructure that meets everyone’s needs and allows for scaling as innovation continues its mad rush forward.