Month: November 2022

Every organization needs to manage its data to get its desired business outcomes. For a company to access its data and use it in day-to-day operations, dashboards, reporting, and data analytics, it either needs a cloud or on-premises solution to facilitate compute, storage, and data management strategies.

What’s The Difference Between The Cloud And On-Premises Data Storage?

On-Premises vs. Cloud—Which Option Best Suits Modern Business Needs?

One mid-market employee shares the story of a server closet that her company had in a previous workplace. For starters, it could be accessed by nearly every employee of the company. She recounted that the IT department placed portable dehumidifiers in the room to keep moisture down. The IT department’s regular practice was to empty the server closet dehumidifiers in the office’s kitchen sink. Unfortunately, a new IT employee happened to trip while carrying one of the dehumidifiers and spilled water all over the server room. Every employee of the company was affected—they found out that the work they had done since the last backup, which happened to be 5 days ago, had disappeared. Even worse, their servers were down for several days after the incident, further impacting their daily business operations.

Although in the past, people feared that cloud would not be secure, or a company would lose control over its data—cloud has proven to be more secure than on-premises hardware. First, cloud vendors host their own data centers and because this is their main business, they have cutting-edge climate control environments to protect their clients’ data. Cloud vendors adhere to frequent hardware replacement turn-over schedules to keep uptime maximized and cloud operations state-of-the-art. Cloud vendors monitor their data centers 24/7/365, are security experts, and have strict controls in place in order to service clients in highly regulated industries with rigorous data security needs. For most mid-sized businesses, it is more cost effective to rely upon the expertise of a cloud vendor for data security and uptime than to host and maintain its own servers, stay on top of the latest security threats, and staff its data center (or data closet) for monitoring to prevent downtime and security breaches.

Large enterprises often can afford to build their own data centers providing them an alternative to an external cloud provider. However, this is incredibly expensive and can set organizations back by USD $10-25 million on yearly setup and operation costs. This infrastructure also takes a lot of time to be implemented and in today’s fast-paced business environment, this might not be entirely acceptable for decision-makers.

Yet, even for enterprises, on-premises solutions no longer make the most sense. Most modern business applications are cloud-native. Cutting-edge data analytics solutions are cloud-native and connect and integrate data sources using cloud technologies. Clouds are better suited for analytics than on-premises hardware, due to scalability and ability to absorb compute spikes (instead of having to invest in hardware with capacity for compute spikes as machine learning algorithms converge—which leads to excess capacity at other times).

Mid-Market Company Considerations

Many organizations are operating in hybrid and multi-cloud environments. This means that they have some data in on-site servers, some data in cloud based line of business applications (relying on the application provider for data storage in whichever cloud the application vendor uses for its product), and many have some data in a public cloud.

However, mid-market companies have added considerations when choosing a cloud solution. Most public cloud service providers do not offer data management services. You need to do this yourself. Yet, mid-market companies often do not have this expert talent in-house. For success, mid-market companies need a cloud hyper-scaler that also provides data engineering services to build data connectors and pipelines, warehouses, data lakes, and the like. This skill set is different from a typical IT employee. Hyper-scalers—who can help organizations with data management, transform data from disparate sources into a decision and analytics-ready status, and bring transactional data into the forefront using a cost-effective cloud solution—tend to be private cloud vendors. For this reason, private cloud solutions make more sense than public cloud for mid-sized organizations.