Cloud and hybrid cloud adoption have been on a continuous rise for years with countless companies seeing the benefits of doing away with enormous and costly onsite data centers in favor of cloud-first solutions. While not all companies want to go “fully” into the cloud, the implementation of the hybrid cloud model, featuring a mix of cloud and on-site physical storage, has been the happy medium in this rise of cloud usage. There are many forms of cloud-based solutions - far too expansive for us to cover them all in this article - but for we’ll highlight a few for the sake of understanding some options.
The first is differentiating between private vs public cloud storage. In private storage, your organization is the only one with direct access to the cloud structure. On the other hand, in a public cloud, the structure your company is utilizing shares space with other users. While the data is secure either way, your company must determine which is best for you. Another thing to consider is the concept of a hybrid cloud environment. Some companies like to maintain local server-based storage in some capacity. Making a decision about the cloud and its capabilities in both storage and analytics solutions should not be taken lightly.
One of the biggest benefits of cloud adoption or adaptation comes in the form of cost savings. Whether it’s direct in the sense you are no longer purchasing, replacing, or maintaining physical on-site data center servers or indirect in the sense that you now have more flexible capital to allocate elsewhere within your business. For example, whenever two companies work on something jointly, whether it’s a full-scale merger or just working with a consultant, sharing data can be challenging. With the ever-growing need for skilled data scientists (which often come in the form of consultants), the importance of flexible and shareable secure data is always on the rise.
Delving a bit deeper into the topic of data science and analytics, this is where modern businesses have been thriving in the predictive analytics it can provide. The first thing any consultant in the field of data science needs to know to understand your project goals is what exactly what your data looks like and what analytics are even possible. Cloud and hybrid cloud-based data storage solutions provide ready and secure access from anywhere in the world without issues common to dealing with private servers and on-site data centers.
Thus, the case is clear that a business can only learn as much as their data allows them to. Even considering costs in this field, much of initial data analytics are exploratory, involving a remote or freelance consultant pulling shared data into a cloud environment running python or another language of their choice. Depending on what type of legacy software paired is with outdated data storage systems, the initial cleaning of this data can be time-consuming but is necessary before any real analytic investigation and exploration can take place.
