Whether you're upgrading existing technology or trying to create something new, data-driven solutions are notoriously difficult, expensive, and risky. With recent technological advancements, there is no reason it should be so stressful. Apollobit’s SaaS Data Enlightenment Platform is an on-demand, all inclusive data ecosystem that makes your job easier by consolidating technology and providing a standardized, simple-to-use data solution applicable to dozens of use-cases. ADEP can simply be turned on and deployed on-premise or in the cloud.
Six integrated interoperable components
ADEP consists of six, key integrated interoperable components, all designed to manage, organize, and activate an organization's data in a user-friendly web-based interface without requiring additional hardware or personnel.
An idea is simply an imaginative thought until someone makes it come to life. Our expert staff will take your product requirements and make your dream come true. We take pride in our ability to execute.
According to recent studies, most data projects fail. Many people know what to say, and know the theory of how it works. However applying the knowledge and ensuring it's done right is difficult and finding resources that understand it is even more difficult. Using ADEP ensures it get's done right.
We once had a client explain that "integration" was a bad word; because it typically translated to 3 years and three million dollars. Regardless of what your data project entails, we promise it will never take 3 years! Apollobit empowers you to get things done faster.
Please contact us and we'll have one of our data experts meet with you face-to-face or over the telephone to discuss how we can make you and your organization a data-driven superstar. We're looking forward to the conversation.
Creating or upgrading data-driven solutions requires time, knowledge, and money; resources most businesses cant afford to waste, especially on a failed Big Data project. The process typically begins by combining various third-party point solutions. All of which do one thing really well, often so well that most of the feature-set never gets used. Technologists are then responsible for producing miracles based off of the imagined requirements of the product owners. To accomplish their herculean task, technologists have to figure out which companies and associations work well together and what can be daisy-chained together, all while staying under budget. Once this arduous task has been completed, a technologist somewhere is required to find the infrastructure, computing power, and experienced personnel to ingrate the data in order for it to be blended, matched, and connected. All of this has to be done, and done successfully before a Big Data solution can actually address the business requirements at hand. In short, the traditional process is a mess. Failure rates are high, but if a company finds success, it is stuck working with a handful of different companies, trying to make all of the technology work together, and managing multiple relationships.